Static Public Member Functions
static void	Rodrigues (Mat src, Mat dst, Mat jacobian)
	Converts a rotation matrix to a rotation vector or vice versa.

static void	Rodrigues (Mat src, Mat dst)
	Converts a rotation matrix to a rotation vector or vice versa.

static Mat	findHomography (MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold, Mat mask, int maxIters, double confidence)
	Finds a perspective transformation between two planes.

static Mat	findHomography (MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold, Mat mask, int maxIters)
	Finds a perspective transformation between two planes.

static Mat	findHomography (MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold, Mat mask)
	Finds a perspective transformation between two planes.

static Mat	findHomography (MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method, double ransacReprojThreshold)
	Finds a perspective transformation between two planes.

static Mat	findHomography (MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, int method)
	Finds a perspective transformation between two planes.

static Mat	findHomography (MatOfPoint2f srcPoints, MatOfPoint2f dstPoints)
	Finds a perspective transformation between two planes.

static Mat	findHomography (MatOfPoint2f srcPoints, MatOfPoint2f dstPoints, Mat mask, UsacParams _params)

static double[]	RQDecomp3x3 (Mat src, Mat mtxR, Mat mtxQ, Mat Qx, Mat Qy, Mat Qz)
	Computes an RQ decomposition of 3x3 matrices.

static double[]	RQDecomp3x3 (Mat src, Mat mtxR, Mat mtxQ, Mat Qx, Mat Qy)
	Computes an RQ decomposition of 3x3 matrices.

static double[]	RQDecomp3x3 (Mat src, Mat mtxR, Mat mtxQ, Mat Qx)
	Computes an RQ decomposition of 3x3 matrices.

static double[]	RQDecomp3x3 (Mat src, Mat mtxR, Mat mtxQ)
	Computes an RQ decomposition of 3x3 matrices.

static void	decomposeProjectionMatrix (Mat projMatrix, Mat cameraMatrix, Mat rotMatrix, Mat transVect, Mat rotMatrixX, Mat rotMatrixY, Mat rotMatrixZ, Mat eulerAngles)
	Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.

static void	decomposeProjectionMatrix (Mat projMatrix, Mat cameraMatrix, Mat rotMatrix, Mat transVect, Mat rotMatrixX, Mat rotMatrixY, Mat rotMatrixZ)
	Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.

static void	decomposeProjectionMatrix (Mat projMatrix, Mat cameraMatrix, Mat rotMatrix, Mat transVect, Mat rotMatrixX, Mat rotMatrixY)
	Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.

static void	decomposeProjectionMatrix (Mat projMatrix, Mat cameraMatrix, Mat rotMatrix, Mat transVect, Mat rotMatrixX)
	Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.

static void	decomposeProjectionMatrix (Mat projMatrix, Mat cameraMatrix, Mat rotMatrix, Mat transVect)
	Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.

static void	matMulDeriv (Mat A, Mat B, Mat dABdA, Mat dABdB)
	Computes partial derivatives of the matrix product for each multiplied matrix.

static void	composeRT (Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2, Mat dr3dt2, Mat dt3dr1, Mat dt3dt1, Mat dt3dr2, Mat dt3dt2)
	Combines two rotation-and-shift transformations.

static void	composeRT (Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2, Mat dr3dt2, Mat dt3dr1, Mat dt3dt1, Mat dt3dr2)
	Combines two rotation-and-shift transformations.

static void	composeRT (Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2, Mat dr3dt2, Mat dt3dr1, Mat dt3dt1)
	Combines two rotation-and-shift transformations.

static void	composeRT (Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2, Mat dr3dt2, Mat dt3dr1)
	Combines two rotation-and-shift transformations.

static void	composeRT (Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2, Mat dr3dt2)
	Combines two rotation-and-shift transformations.

static void	composeRT (Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1, Mat dr3dr2)
	Combines two rotation-and-shift transformations.

static void	composeRT (Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1, Mat dr3dt1)
	Combines two rotation-and-shift transformations.

static void	composeRT (Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3, Mat dr3dr1)
	Combines two rotation-and-shift transformations.

static void	composeRT (Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3)
	Combines two rotation-and-shift transformations.

static void	projectPoints (MatOfPoint3f objectPoints, Mat rvec, Mat tvec, Mat cameraMatrix, MatOfDouble distCoeffs, MatOfPoint2f imagePoints, Mat jacobian, double aspectRatio)
	Projects 3D points to an image plane.

static void	projectPoints (MatOfPoint3f objectPoints, Mat rvec, Mat tvec, Mat cameraMatrix, MatOfDouble distCoeffs, MatOfPoint2f imagePoints, Mat jacobian)
	Projects 3D points to an image plane.

static void	projectPoints (MatOfPoint3f objectPoints, Mat rvec, Mat tvec, Mat cameraMatrix, MatOfDouble distCoeffs, MatOfPoint2f imagePoints)
	Projects 3D points to an image plane.

static bool	solvePnP (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess, int flags)
	Finds an object pose from 3D-2D point correspondences.

static bool	solvePnP (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess)
	Finds an object pose from 3D-2D point correspondences.

static bool	solvePnP (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec)
	Finds an object pose from 3D-2D point correspondences.

static bool	solvePnPRansac (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess, int iterationsCount, float reprojectionError, double confidence, Mat inliers, int flags)
	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.

static bool	solvePnPRansac (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess, int iterationsCount, float reprojectionError, double confidence, Mat inliers)
	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.

static bool	solvePnPRansac (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess, int iterationsCount, float reprojectionError, double confidence)
	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.

static bool	solvePnPRansac (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess, int iterationsCount, float reprojectionError)
	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.

static bool	solvePnPRansac (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess, int iterationsCount)
	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.

static bool	solvePnPRansac (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess)
	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.

static bool	solvePnPRansac (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec)
	Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.

static bool	solvePnPRansac (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, Mat inliers, UsacParams _params)

static bool	solvePnPRansac (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, Mat inliers)

static int	solveP3P (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, int flags)
	Finds an object pose from 3 3D-2D point correspondences.

static void	solvePnPRefineLM (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, TermCriteria criteria)
	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

static void	solvePnPRefineLM (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec)
	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

static void	solvePnPRefineVVS (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, TermCriteria criteria, double VVSlambda)
	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

static void	solvePnPRefineVVS (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, TermCriteria criteria)
	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

static void	solvePnPRefineVVS (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec)
	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

static int	solvePnPGeneric (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, bool useExtrinsicGuess, int flags, Mat rvec, Mat tvec, Mat reprojectionError)
	Finds an object pose from 3D-2D point correspondences.

static int	solvePnPGeneric (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, bool useExtrinsicGuess, int flags, Mat rvec, Mat tvec)
	Finds an object pose from 3D-2D point correspondences.

static int	solvePnPGeneric (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, bool useExtrinsicGuess, int flags, Mat rvec)
	Finds an object pose from 3D-2D point correspondences.

static int	solvePnPGeneric (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, bool useExtrinsicGuess, int flags)
	Finds an object pose from 3D-2D point correspondences.

static int	solvePnPGeneric (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, bool useExtrinsicGuess)
	Finds an object pose from 3D-2D point correspondences.

static int	solvePnPGeneric (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs)
	Finds an object pose from 3D-2D point correspondences.

static Mat	initCameraMatrix2D (List< MatOfPoint3f > objectPoints, List< MatOfPoint2f > imagePoints, Size imageSize, double aspectRatio)
	Finds an initial camera intrinsic matrix from 3D-2D point correspondences.

static Mat	initCameraMatrix2D (List< MatOfPoint3f > objectPoints, List< MatOfPoint2f > imagePoints, Size imageSize)
	Finds an initial camera intrinsic matrix from 3D-2D point correspondences.

static bool	findChessboardCorners (Mat image, Size patternSize, MatOfPoint2f corners, int flags)
	Finds the positions of internal corners of the chessboard.

static bool	findChessboardCorners (Mat image, Size patternSize, MatOfPoint2f corners)
	Finds the positions of internal corners of the chessboard.

static bool	checkChessboard (Mat img, Size size)

static bool	findChessboardCornersSBWithMeta (Mat image, Size patternSize, Mat corners, int flags, Mat meta)
	Finds the positions of internal corners of the chessboard using a sector based approach.

static bool	findChessboardCornersSB (Mat image, Size patternSize, Mat corners, int flags)

static bool	findChessboardCornersSB (Mat image, Size patternSize, Mat corners)

static Scalar	estimateChessboardSharpness (Mat image, Size patternSize, Mat corners, float rise_distance, bool vertical, Mat sharpness)
	Estimates the sharpness of a detected chessboard.

static Scalar	estimateChessboardSharpness (Mat image, Size patternSize, Mat corners, float rise_distance, bool vertical)
	Estimates the sharpness of a detected chessboard.

static Scalar	estimateChessboardSharpness (Mat image, Size patternSize, Mat corners, float rise_distance)
	Estimates the sharpness of a detected chessboard.

static Scalar	estimateChessboardSharpness (Mat image, Size patternSize, Mat corners)
	Estimates the sharpness of a detected chessboard.

static bool	find4QuadCornerSubpix (Mat img, Mat corners, Size region_size)

static void	drawChessboardCorners (Mat image, Size patternSize, MatOfPoint2f corners, bool patternWasFound)
	Renders the detected chessboard corners.

static void	drawFrameAxes (Mat image, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, float length, int thickness)
	Draw axes of the world/object coordinate system from pose estimation.

static void	drawFrameAxes (Mat image, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, float length)
	Draw axes of the world/object coordinate system from pose estimation.

static bool	findCirclesGrid (Mat image, Size patternSize, Mat centers, int flags)

static bool	findCirclesGrid (Mat image, Size patternSize, Mat centers)

static double	calibrateCameraExtended (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags, TermCriteria criteria)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraExtended (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraExtended (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCamera (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, int flags, TermCriteria criteria)

static double	calibrateCamera (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, int flags)

static double	calibrateCamera (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs)

static double	calibrateCameraROExtended (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors, int flags, TermCriteria criteria)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraROExtended (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors, int flags)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraROExtended (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraRO (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, int flags, TermCriteria criteria)

static double	calibrateCameraRO (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, int flags)

static double	calibrateCameraRO (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints)

static void	calibrationMatrixValues (Mat cameraMatrix, Size imageSize, double apertureWidth, double apertureHeight, double[] fovx, double[] fovy, double[] focalLength, Point principalPoint, double[] aspectRatio)
	Computes useful camera characteristics from the camera intrinsic matrix.

static double	stereoCalibrateExtended (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, List< Mat > rvecs, List< Mat > tvecs, Mat perViewErrors, int flags, TermCriteria criteria)
	Calibrates a stereo camera set up. This function finds the intrinsic parameters for each of the two cameras and the extrinsic parameters between the two cameras.

static double	stereoCalibrateExtended (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, List< Mat > rvecs, List< Mat > tvecs, Mat perViewErrors, int flags)
	Calibrates a stereo camera set up. This function finds the intrinsic parameters for each of the two cameras and the extrinsic parameters between the two cameras.

static double	stereoCalibrateExtended (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, List< Mat > rvecs, List< Mat > tvecs, Mat perViewErrors)
	Calibrates a stereo camera set up. This function finds the intrinsic parameters for each of the two cameras and the extrinsic parameters between the two cameras.

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, int flags, TermCriteria criteria)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, int flags)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors, int flags, TermCriteria criteria)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors, int flags)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors)

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, Size newImageSize, Rect validPixROI1, Rect validPixROI2)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, Size newImageSize, Rect validPixROI1)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, Size newImageSize)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Size imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q)
	Computes rectification transforms for each head of a calibrated stereo camera.

static bool	stereoRectifyUncalibrated (Mat points1, Mat points2, Mat F, Size imgSize, Mat H1, Mat H2, double threshold)
	Computes a rectification transform for an uncalibrated stereo camera.

static bool	stereoRectifyUncalibrated (Mat points1, Mat points2, Mat F, Size imgSize, Mat H1, Mat H2)
	Computes a rectification transform for an uncalibrated stereo camera.

static float	rectify3Collinear (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Mat cameraMatrix3, Mat distCoeffs3, List< Mat > imgpt1, List< Mat > imgpt3, Size imageSize, Mat R12, Mat T12, Mat R13, Mat T13, Mat R1, Mat R2, Mat R3, Mat P1, Mat P2, Mat P3, Mat Q, double alpha, Size newImgSize, Rect roi1, Rect roi2, int flags)

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha, Size newImgSize, Rect validPixROI, bool centerPrincipalPoint)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha, Size newImgSize, Rect validPixROI)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha, Size newImgSize)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, Size imageSize, double alpha)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static void	calibrateHandEye (List< Mat > R_gripper2base, List< Mat > t_gripper2base, List< Mat > R_target2cam, List< Mat > t_target2cam, Mat R_cam2gripper, Mat t_cam2gripper, int method)
	Computes Hand-Eye calibration: \(_{}^{g}\textrm{T}_c\).

static void	calibrateHandEye (List< Mat > R_gripper2base, List< Mat > t_gripper2base, List< Mat > R_target2cam, List< Mat > t_target2cam, Mat R_cam2gripper, Mat t_cam2gripper)
	Computes Hand-Eye calibration: \(_{}^{g}\textrm{T}_c\).

static void	calibrateRobotWorldHandEye (List< Mat > R_world2cam, List< Mat > t_world2cam, List< Mat > R_base2gripper, List< Mat > t_base2gripper, Mat R_base2world, Mat t_base2world, Mat R_gripper2cam, Mat t_gripper2cam, int method)
	Computes Robot-World/Hand-Eye calibration: \(_{}^{w}\textrm{T}_b\) and \(_{}^{c}\textrm{T}_g\).

static void	calibrateRobotWorldHandEye (List< Mat > R_world2cam, List< Mat > t_world2cam, List< Mat > R_base2gripper, List< Mat > t_base2gripper, Mat R_base2world, Mat t_base2world, Mat R_gripper2cam, Mat t_gripper2cam)
	Computes Robot-World/Hand-Eye calibration: \(_{}^{w}\textrm{T}_b\) and \(_{}^{c}\textrm{T}_g\).

static void	convertPointsToHomogeneous (Mat src, Mat dst)
	Converts points from Euclidean to homogeneous space.

static void	convertPointsFromHomogeneous (Mat src, Mat dst)
	Converts points from homogeneous to Euclidean space.

static Mat	findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold, double confidence, int maxIters, Mat mask)
	Calculates a fundamental matrix from the corresponding points in two images.

static Mat	findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold, double confidence, int maxIters)
	Calculates a fundamental matrix from the corresponding points in two images.

static Mat	findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold, double confidence, Mat mask)

static Mat	findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold, double confidence)

static Mat	findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold)

static Mat	findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2, int method)

static Mat	findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2)

static Mat	findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2, Mat mask, UsacParams _params)

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix, int method, double prob, double threshold, int maxIters, Mat mask)
	Calculates an essential matrix from the corresponding points in two images.

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix, int method, double prob, double threshold, int maxIters)
	Calculates an essential matrix from the corresponding points in two images.

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix, int method, double prob, double threshold)
	Calculates an essential matrix from the corresponding points in two images.

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix, int method, double prob)
	Calculates an essential matrix from the corresponding points in two images.

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix, int method)
	Calculates an essential matrix from the corresponding points in two images.

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix)
	Calculates an essential matrix from the corresponding points in two images.

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, Point pp, int method, double prob, double threshold, int maxIters, Mat mask)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, Point pp, int method, double prob, double threshold, int maxIters)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, Point pp, int method, double prob, double threshold)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, Point pp, int method, double prob)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, Point pp, int method)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, Point pp)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal)

static Mat	findEssentialMat (Mat points1, Mat points2)

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method, double prob, double threshold, Mat mask)
	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method, double prob, double threshold)
	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method, double prob)
	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, int method)
	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2)
	Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.

static Mat	findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix1, Mat cameraMatrix2, Mat dist_coeff1, Mat dist_coeff2, Mat mask, UsacParams _params)

static void	decomposeEssentialMat (Mat E, Mat R1, Mat R2, Mat t)
	Decompose an essential matrix to possible rotations and translation.

static int	recoverPose (Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Mat E, Mat R, Mat t, int method, double prob, double threshold, Mat mask)
	Recovers the relative camera rotation and the translation from corresponding points in two images from two different cameras, using cheirality check. Returns the number of inliers that pass the check.

static int	recoverPose (Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Mat E, Mat R, Mat t, int method, double prob, double threshold)
	Recovers the relative camera rotation and the translation from corresponding points in two images from two different cameras, using cheirality check. Returns the number of inliers that pass the check.

static int	recoverPose (Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Mat E, Mat R, Mat t, int method, double prob)
	Recovers the relative camera rotation and the translation from corresponding points in two images from two different cameras, using cheirality check. Returns the number of inliers that pass the check.

static int	recoverPose (Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Mat E, Mat R, Mat t, int method)
	Recovers the relative camera rotation and the translation from corresponding points in two images from two different cameras, using cheirality check. Returns the number of inliers that pass the check.

static int	recoverPose (Mat points1, Mat points2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Mat E, Mat R, Mat t)
	Recovers the relative camera rotation and the translation from corresponding points in two images from two different cameras, using cheirality check. Returns the number of inliers that pass the check.

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat cameraMatrix, Mat R, Mat t, Mat mask)
	Recovers the relative camera rotation and the translation from an estimated essential matrix and the corresponding points in two images, using chirality check. Returns the number of inliers that pass the check.

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat cameraMatrix, Mat R, Mat t)
	Recovers the relative camera rotation and the translation from an estimated essential matrix and the corresponding points in two images, using chirality check. Returns the number of inliers that pass the check.

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat R, Mat t, double focal, Point pp, Mat mask)

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat R, Mat t, double focal, Point pp)

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat R, Mat t, double focal)

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat R, Mat t)

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat cameraMatrix, Mat R, Mat t, double distanceThresh, Mat mask, Mat triangulatedPoints)

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat cameraMatrix, Mat R, Mat t, double distanceThresh, Mat mask)

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat cameraMatrix, Mat R, Mat t, double distanceThresh)

static void	computeCorrespondEpilines (Mat points, int whichImage, Mat F, Mat lines)
	For points in an image of a stereo pair, computes the corresponding epilines in the other image.

static void	triangulatePoints (Mat projMatr1, Mat projMatr2, Mat projPoints1, Mat projPoints2, Mat points4D)
	This function reconstructs 3-dimensional points (in homogeneous coordinates) by using their observations with a stereo camera.

static void	correctMatches (Mat F, Mat points1, Mat points2, Mat newPoints1, Mat newPoints2)
	Refines coordinates of corresponding points.

static void	filterSpeckles (Mat img, double newVal, int maxSpeckleSize, double maxDiff, Mat buf)
	Filters off small noise blobs (speckles) in the disparity map.

static void	filterSpeckles (Mat img, double newVal, int maxSpeckleSize, double maxDiff)
	Filters off small noise blobs (speckles) in the disparity map.

static Rect	getValidDisparityROI (Rect roi1, Rect roi2, int minDisparity, int numberOfDisparities, int blockSize)

static void	validateDisparity (Mat disparity, Mat cost, int minDisparity, int numberOfDisparities, int disp12MaxDisp)

static void	validateDisparity (Mat disparity, Mat cost, int minDisparity, int numberOfDisparities)

static void	reprojectImageTo3D (Mat disparity, Mat _3dImage, Mat Q, bool handleMissingValues, int ddepth)
	Reprojects a disparity image to 3D space.

static void	reprojectImageTo3D (Mat disparity, Mat _3dImage, Mat Q, bool handleMissingValues)
	Reprojects a disparity image to 3D space.

static void	reprojectImageTo3D (Mat disparity, Mat _3dImage, Mat Q)
	Reprojects a disparity image to 3D space.

static double	sampsonDistance (Mat pt1, Mat pt2, Mat F)
	Calculates the Sampson Distance between two points.

static int	estimateAffine3D (Mat src, Mat dst, Mat _out, Mat inliers, double ransacThreshold, double confidence)
	Computes an optimal affine transformation between two 3D point sets.

static int	estimateAffine3D (Mat src, Mat dst, Mat _out, Mat inliers, double ransacThreshold)
	Computes an optimal affine transformation between two 3D point sets.

static int	estimateAffine3D (Mat src, Mat dst, Mat _out, Mat inliers)
	Computes an optimal affine transformation between two 3D point sets.

static Mat	estimateAffine3D (Mat src, Mat dst, double[] scale, bool force_rotation)
	Computes an optimal affine transformation between two 3D point sets.

static Mat	estimateAffine3D (Mat src, Mat dst, double[] scale)
	Computes an optimal affine transformation between two 3D point sets.

static Mat	estimateAffine3D (Mat src, Mat dst)
	Computes an optimal affine transformation between two 3D point sets.

static int	estimateTranslation3D (Mat src, Mat dst, Mat _out, Mat inliers, double ransacThreshold, double confidence)
	Computes an optimal translation between two 3D point sets.

static int	estimateTranslation3D (Mat src, Mat dst, Mat _out, Mat inliers, double ransacThreshold)
	Computes an optimal translation between two 3D point sets.

static int	estimateTranslation3D (Mat src, Mat dst, Mat _out, Mat inliers)
	Computes an optimal translation between two 3D point sets.

static Mat	estimateAffine2D (Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence, long refineIters)
	Computes an optimal affine transformation between two 2D point sets.

static Mat	estimateAffine2D (Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence)
	Computes an optimal affine transformation between two 2D point sets.

static Mat	estimateAffine2D (Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters)
	Computes an optimal affine transformation between two 2D point sets.

static Mat	estimateAffine2D (Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold)
	Computes an optimal affine transformation between two 2D point sets.

static Mat	estimateAffine2D (Mat from, Mat to, Mat inliers, int method)
	Computes an optimal affine transformation between two 2D point sets.

static Mat	estimateAffine2D (Mat from, Mat to, Mat inliers)
	Computes an optimal affine transformation between two 2D point sets.

static Mat	estimateAffine2D (Mat from, Mat to)
	Computes an optimal affine transformation between two 2D point sets.

static Mat	estimateAffine2D (Mat pts1, Mat pts2, Mat inliers, UsacParams _params)

static Mat	estimateAffinePartial2D (Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence, long refineIters)
	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.

static Mat	estimateAffinePartial2D (Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters, double confidence)
	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.

static Mat	estimateAffinePartial2D (Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold, long maxIters)
	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.

static Mat	estimateAffinePartial2D (Mat from, Mat to, Mat inliers, int method, double ransacReprojThreshold)
	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.

static Mat	estimateAffinePartial2D (Mat from, Mat to, Mat inliers, int method)
	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.

static Mat	estimateAffinePartial2D (Mat from, Mat to, Mat inliers)
	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.

static Mat	estimateAffinePartial2D (Mat from, Mat to)
	Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.

static int	decomposeHomographyMat (Mat H, Mat K, List< Mat > rotations, List< Mat > translations, List< Mat > normals)
	Decompose a homography matrix to rotation(s), translation(s) and plane normal(s).

static void	filterHomographyDecompByVisibleRefpoints (List< Mat > rotations, List< Mat > normals, Mat beforePoints, Mat afterPoints, Mat possibleSolutions, Mat pointsMask)
	Filters homography decompositions based on additional information.

static void	filterHomographyDecompByVisibleRefpoints (List< Mat > rotations, List< Mat > normals, Mat beforePoints, Mat afterPoints, Mat possibleSolutions)
	Filters homography decompositions based on additional information.

static void	undistort (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, Mat newCameraMatrix)
	Transforms an image to compensate for lens distortion.

static void	undistort (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs)
	Transforms an image to compensate for lens distortion.

static void	initUndistortRectifyMap (Mat cameraMatrix, Mat distCoeffs, Mat R, Mat newCameraMatrix, Size size, int m1type, Mat map1, Mat map2)
	Computes the undistortion and rectification transformation map.

static void	initInverseRectificationMap (Mat cameraMatrix, Mat distCoeffs, Mat R, Mat newCameraMatrix, Size size, int m1type, Mat map1, Mat map2)
	Computes the projection and inverse-rectification transformation map. In essense, this is the inverse of initUndistortRectifyMap to accomodate stereo-rectification of projectors ('inverse-cameras') in projector-camera pairs.

static Mat	getDefaultNewCameraMatrix (Mat cameraMatrix, Size imgsize, bool centerPrincipalPoint)
	Returns the default new camera matrix.

static Mat	getDefaultNewCameraMatrix (Mat cameraMatrix, Size imgsize)
	Returns the default new camera matrix.

static Mat	getDefaultNewCameraMatrix (Mat cameraMatrix)
	Returns the default new camera matrix.

static void	undistortPoints (MatOfPoint2f src, MatOfPoint2f dst, Mat cameraMatrix, Mat distCoeffs, Mat R, Mat P)
	Computes the ideal point coordinates from the observed point coordinates.

static void	undistortPoints (MatOfPoint2f src, MatOfPoint2f dst, Mat cameraMatrix, Mat distCoeffs, Mat R)
	Computes the ideal point coordinates from the observed point coordinates.

static void	undistortPoints (MatOfPoint2f src, MatOfPoint2f dst, Mat cameraMatrix, Mat distCoeffs)
	Computes the ideal point coordinates from the observed point coordinates.

static void	undistortPointsIter (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, Mat R, Mat P, TermCriteria criteria)

static void	undistortImagePoints (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, TermCriteria arg1)
	Compute undistorted image points position.

static void	undistortImagePoints (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs)
	Compute undistorted image points position.

static void	fisheye_projectPoints (Mat objectPoints, Mat imagePoints, Mat rvec, Mat tvec, Mat K, Mat D, double alpha, Mat jacobian)

static void	fisheye_projectPoints (Mat objectPoints, Mat imagePoints, Mat rvec, Mat tvec, Mat K, Mat D, double alpha)

static void	fisheye_projectPoints (Mat objectPoints, Mat imagePoints, Mat rvec, Mat tvec, Mat K, Mat D)

static void	fisheye_distortPoints (Mat undistorted, Mat distorted, Mat K, Mat D, double alpha)
	Distorts 2D points using fisheye model.

static void	fisheye_distortPoints (Mat undistorted, Mat distorted, Mat K, Mat D)
	Distorts 2D points using fisheye model.

static void	fisheye_undistortPoints (Mat distorted, Mat undistorted, Mat K, Mat D, Mat R, Mat P, TermCriteria criteria)
	Undistorts 2D points using fisheye model.

static void	fisheye_undistortPoints (Mat distorted, Mat undistorted, Mat K, Mat D, Mat R, Mat P)
	Undistorts 2D points using fisheye model.

static void	fisheye_undistortPoints (Mat distorted, Mat undistorted, Mat K, Mat D, Mat R)
	Undistorts 2D points using fisheye model.

static void	fisheye_undistortPoints (Mat distorted, Mat undistorted, Mat K, Mat D)
	Undistorts 2D points using fisheye model.

static void	fisheye_initUndistortRectifyMap (Mat K, Mat D, Mat R, Mat P, Size size, int m1type, Mat map1, Mat map2)
	Computes undistortion and rectification maps for image transform by #remap. If D is empty zero distortion is used, if R or P is empty identity matrixes are used.

static void	fisheye_undistortImage (Mat distorted, Mat undistorted, Mat K, Mat D, Mat Knew, Size new_size)
	Transforms an image to compensate for fisheye lens distortion.

static void	fisheye_undistortImage (Mat distorted, Mat undistorted, Mat K, Mat D, Mat Knew)
	Transforms an image to compensate for fisheye lens distortion.

static void	fisheye_undistortImage (Mat distorted, Mat undistorted, Mat K, Mat D)
	Transforms an image to compensate for fisheye lens distortion.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, Size image_size, Mat R, Mat P, double balance, Size new_size, double fov_scale)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, Size image_size, Mat R, Mat P, double balance, Size new_size)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, Size image_size, Mat R, Mat P, double balance)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, Size image_size, Mat R, Mat P)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static double	fisheye_calibrate (List< Mat > objectPoints, List< Mat > imagePoints, Size image_size, Mat K, Mat D, List< Mat > rvecs, List< Mat > tvecs, int flags, TermCriteria criteria)
	Performs camera calibration.

static double	fisheye_calibrate (List< Mat > objectPoints, List< Mat > imagePoints, Size image_size, Mat K, Mat D, List< Mat > rvecs, List< Mat > tvecs, int flags)
	Performs camera calibration.

static double	fisheye_calibrate (List< Mat > objectPoints, List< Mat > imagePoints, Size image_size, Mat K, Mat D, List< Mat > rvecs, List< Mat > tvecs)
	Performs camera calibration.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, Size newImageSize, double balance, double fov_scale)
	Stereo rectification for fisheye camera model.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, Size newImageSize, double balance)
	Stereo rectification for fisheye camera model.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, Size newImageSize)
	Stereo rectification for fisheye camera model.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags)
	Stereo rectification for fisheye camera model.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T, List< Mat > rvecs, List< Mat > tvecs, int flags, TermCriteria criteria)
	Performs stereo calibration.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T, List< Mat > rvecs, List< Mat > tvecs, int flags)
	Performs stereo calibration.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T, List< Mat > rvecs, List< Mat > tvecs)
	Performs stereo calibration.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T, int flags, TermCriteria criteria)

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T, int flags)

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, Size imageSize, Mat R, Mat T)

static bool	fisheye_solvePnP (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess, int flags, TermCriteria criteria)
	Finds an object pose from 3D-2D point correspondences for fisheye camera moodel.

static bool	fisheye_solvePnP (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess, int flags)
	Finds an object pose from 3D-2D point correspondences for fisheye camera moodel.

static bool	fisheye_solvePnP (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess)
	Finds an object pose from 3D-2D point correspondences for fisheye camera moodel.

static bool	fisheye_solvePnP (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec)
	Finds an object pose from 3D-2D point correspondences for fisheye camera moodel.

static void	solvePnPRefineLM (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, in Vec3d criteria)
	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

static void	solvePnPRefineVVS (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, in Vec3d criteria, double VVSlambda)
	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

static void	solvePnPRefineVVS (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, in Vec3d criteria)
	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

static Mat	initCameraMatrix2D (List< MatOfPoint3f > objectPoints, List< MatOfPoint2f > imagePoints, in Vec2d imageSize, double aspectRatio)
	Finds an initial camera intrinsic matrix from 3D-2D point correspondences.

static Mat	initCameraMatrix2D (List< MatOfPoint3f > objectPoints, List< MatOfPoint2f > imagePoints, in Vec2d imageSize)
	Finds an initial camera intrinsic matrix from 3D-2D point correspondences.

static bool	findChessboardCorners (Mat image, in Vec2d patternSize, MatOfPoint2f corners, int flags)
	Finds the positions of internal corners of the chessboard.

static bool	findChessboardCorners (Mat image, in Vec2d patternSize, MatOfPoint2f corners)
	Finds the positions of internal corners of the chessboard.

static bool	checkChessboard (Mat img, in Vec2d size)

static bool	findChessboardCornersSBWithMeta (Mat image, in Vec2d patternSize, Mat corners, int flags, Mat meta)
	Finds the positions of internal corners of the chessboard using a sector based approach.

static bool	findChessboardCornersSB (Mat image, in Vec2d patternSize, Mat corners, int flags)

static bool	findChessboardCornersSB (Mat image, in Vec2d patternSize, Mat corners)

static Vec4d	estimateChessboardSharpnessAsVec4d (Mat image, in Vec2d patternSize, Mat corners, float rise_distance, bool vertical, Mat sharpness)
	Estimates the sharpness of a detected chessboard.

static Vec4d	estimateChessboardSharpnessAsVec4d (Mat image, in Vec2d patternSize, Mat corners, float rise_distance, bool vertical)
	Estimates the sharpness of a detected chessboard.

static Vec4d	estimateChessboardSharpnessAsVec4d (Mat image, in Vec2d patternSize, Mat corners, float rise_distance)
	Estimates the sharpness of a detected chessboard.

static Vec4d	estimateChessboardSharpnessAsVec4d (Mat image, in Vec2d patternSize, Mat corners)
	Estimates the sharpness of a detected chessboard.

static bool	find4QuadCornerSubpix (Mat img, Mat corners, in Vec2d region_size)

static void	drawChessboardCorners (Mat image, in Vec2d patternSize, MatOfPoint2f corners, bool patternWasFound)
	Renders the detected chessboard corners.

static bool	findCirclesGrid (Mat image, in Vec2d patternSize, Mat centers, int flags)

static bool	findCirclesGrid (Mat image, in Vec2d patternSize, Mat centers)

static double	calibrateCameraExtended (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags, in Vec3d criteria)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraExtended (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraExtended (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCamera (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, int flags, in Vec3d criteria)

static double	calibrateCamera (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, int flags)

static double	calibrateCamera (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs)

static double	calibrateCameraROExtended (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors, int flags, in Vec3d criteria)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraROExtended (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors, int flags)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraROExtended (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraRO (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, int flags, in Vec3d criteria)

static double	calibrateCameraRO (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, int flags)

static double	calibrateCameraRO (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints)

static void	calibrationMatrixValues (Mat cameraMatrix, in Vec2d imageSize, double apertureWidth, double apertureHeight, double[] fovx, double[] fovy, double[] focalLength, out Vec2d principalPoint, double[] aspectRatio)
	Computes useful camera characteristics from the camera intrinsic matrix.

static double	stereoCalibrateExtended (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat E, Mat F, List< Mat > rvecs, List< Mat > tvecs, Mat perViewErrors, int flags, in Vec3d criteria)
	Calibrates a stereo camera set up. This function finds the intrinsic parameters for each of the two cameras and the extrinsic parameters between the two cameras.

static double	stereoCalibrateExtended (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat E, Mat F, List< Mat > rvecs, List< Mat > tvecs, Mat perViewErrors, int flags)
	Calibrates a stereo camera set up. This function finds the intrinsic parameters for each of the two cameras and the extrinsic parameters between the two cameras.

static double	stereoCalibrateExtended (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat E, Mat F, List< Mat > rvecs, List< Mat > tvecs, Mat perViewErrors)
	Calibrates a stereo camera set up. This function finds the intrinsic parameters for each of the two cameras and the extrinsic parameters between the two cameras.

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat E, Mat F, int flags, in Vec3d criteria)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat E, Mat F, int flags)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat E, Mat F)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors, int flags, in Vec3d criteria)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors, int flags)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors)

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, in Vec2d newImageSize, out Vec4i validPixROI1, out Vec4i validPixROI2)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, in Vec2d newImageSize, out Vec4i validPixROI1)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, in Vec2d newImageSize)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in Vec2d imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q)
	Computes rectification transforms for each head of a calibrated stereo camera.

static bool	stereoRectifyUncalibrated (Mat points1, Mat points2, Mat F, in Vec2d imgSize, Mat H1, Mat H2, double threshold)
	Computes a rectification transform for an uncalibrated stereo camera.

static bool	stereoRectifyUncalibrated (Mat points1, Mat points2, Mat F, in Vec2d imgSize, Mat H1, Mat H2)
	Computes a rectification transform for an uncalibrated stereo camera.

static float	rectify3Collinear (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Mat cameraMatrix3, Mat distCoeffs3, List< Mat > imgpt1, List< Mat > imgpt3, in Vec2d imageSize, Mat R12, Mat T12, Mat R13, Mat T13, Mat R1, Mat R2, Mat R3, Mat P1, Mat P2, Mat P3, Mat Q, double alpha, in Vec2d newImgSize, out Vec4i roi1, out Vec4i roi2, int flags)

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, in Vec2d imageSize, double alpha, in Vec2d newImgSize, out Vec4i validPixROI, bool centerPrincipalPoint)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, in Vec2d imageSize, double alpha, in Vec2d newImgSize, out Vec4i validPixROI)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, in Vec2d imageSize, double alpha, in Vec2d newImgSize)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, in Vec2d imageSize, double alpha)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in Vec2d pp, int method, double prob, double threshold, int maxIters, Mat mask)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in Vec2d pp, int method, double prob, double threshold, int maxIters)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in Vec2d pp, int method, double prob, double threshold)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in Vec2d pp, int method, double prob)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in Vec2d pp, int method)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in Vec2d pp)

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat R, Mat t, double focal, in Vec2d pp, Mat mask)

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat R, Mat t, double focal, in Vec2d pp)

static Vec4i	getValidDisparityROIAsVec4i (in Vec4i roi1, Vec4i roi2, int minDisparity, int numberOfDisparities, int blockSize)

static void	initUndistortRectifyMap (Mat cameraMatrix, Mat distCoeffs, Mat R, Mat newCameraMatrix, in Vec2d size, int m1type, Mat map1, Mat map2)
	Computes the undistortion and rectification transformation map.

static void	initInverseRectificationMap (Mat cameraMatrix, Mat distCoeffs, Mat R, Mat newCameraMatrix, in Vec2d size, int m1type, Mat map1, Mat map2)
	Computes the projection and inverse-rectification transformation map. In essense, this is the inverse of initUndistortRectifyMap to accomodate stereo-rectification of projectors ('inverse-cameras') in projector-camera pairs.

static Mat	getDefaultNewCameraMatrix (Mat cameraMatrix, in Vec2d imgsize, bool centerPrincipalPoint)
	Returns the default new camera matrix.

static Mat	getDefaultNewCameraMatrix (Mat cameraMatrix, in Vec2d imgsize)
	Returns the default new camera matrix.

static void	undistortPointsIter (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, Mat R, Mat P, in Vec3d criteria)

static void	undistortImagePoints (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, in Vec3d arg1)
	Compute undistorted image points position.

static void	fisheye_undistortPoints (Mat distorted, Mat undistorted, Mat K, Mat D, Mat R, Mat P, in Vec3d criteria)
	Undistorts 2D points using fisheye model.

static void	fisheye_initUndistortRectifyMap (Mat K, Mat D, Mat R, Mat P, in Vec2d size, int m1type, Mat map1, Mat map2)
	Computes undistortion and rectification maps for image transform by #remap. If D is empty zero distortion is used, if R or P is empty identity matrixes are used.

static void	fisheye_undistortImage (Mat distorted, Mat undistorted, Mat K, Mat D, Mat Knew, in Vec2d new_size)
	Transforms an image to compensate for fisheye lens distortion.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, in Vec2d image_size, Mat R, Mat P, double balance, in Vec2d new_size, double fov_scale)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, in Vec2d image_size, Mat R, Mat P, double balance, in Vec2d new_size)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, in Vec2d image_size, Mat R, Mat P, double balance)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, in Vec2d image_size, Mat R, Mat P)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static double	fisheye_calibrate (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d image_size, Mat K, Mat D, List< Mat > rvecs, List< Mat > tvecs, int flags, in Vec3d criteria)
	Performs camera calibration.

static double	fisheye_calibrate (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d image_size, Mat K, Mat D, List< Mat > rvecs, List< Mat > tvecs, int flags)
	Performs camera calibration.

static double	fisheye_calibrate (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d image_size, Mat K, Mat D, List< Mat > rvecs, List< Mat > tvecs)
	Performs camera calibration.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, in Vec2d imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, in Vec2d newImageSize, double balance, double fov_scale)
	Stereo rectification for fisheye camera model.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, in Vec2d imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, in Vec2d newImageSize, double balance)
	Stereo rectification for fisheye camera model.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, in Vec2d imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, in Vec2d newImageSize)
	Stereo rectification for fisheye camera model.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, in Vec2d imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags)
	Stereo rectification for fisheye camera model.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in Vec2d imageSize, Mat R, Mat T, List< Mat > rvecs, List< Mat > tvecs, int flags, in Vec3d criteria)
	Performs stereo calibration.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in Vec2d imageSize, Mat R, Mat T, List< Mat > rvecs, List< Mat > tvecs, int flags)
	Performs stereo calibration.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in Vec2d imageSize, Mat R, Mat T, List< Mat > rvecs, List< Mat > tvecs)
	Performs stereo calibration.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in Vec2d imageSize, Mat R, Mat T, int flags, in Vec3d criteria)

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in Vec2d imageSize, Mat R, Mat T, int flags)

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in Vec2d imageSize, Mat R, Mat T)

static bool	fisheye_solvePnP (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess, int flags, in Vec3d criteria)
	Finds an object pose from 3D-2D point correspondences for fisheye camera moodel.

static void	solvePnPRefineLM (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, in(double type, double maxCount, double epsilon) criteria)
	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

static void	solvePnPRefineVVS (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, in(double type, double maxCount, double epsilon) criteria, double VVSlambda)
	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

static void	solvePnPRefineVVS (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, in(double type, double maxCount, double epsilon) criteria)
	Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

static Mat	initCameraMatrix2D (List< MatOfPoint3f > objectPoints, List< MatOfPoint2f > imagePoints, in(double width, double height) imageSize, double aspectRatio)
	Finds an initial camera intrinsic matrix from 3D-2D point correspondences.

static Mat	initCameraMatrix2D (List< MatOfPoint3f > objectPoints, List< MatOfPoint2f > imagePoints, in(double width, double height) imageSize)
	Finds an initial camera intrinsic matrix from 3D-2D point correspondences.

static bool	findChessboardCorners (Mat image, in(double width, double height) patternSize, MatOfPoint2f corners, int flags)
	Finds the positions of internal corners of the chessboard.

static bool	findChessboardCorners (Mat image, in(double width, double height) patternSize, MatOfPoint2f corners)
	Finds the positions of internal corners of the chessboard.

static bool	checkChessboard (Mat img, in(double width, double height) size)

static bool	findChessboardCornersSBWithMeta (Mat image, in(double width, double height) patternSize, Mat corners, int flags, Mat meta)
	Finds the positions of internal corners of the chessboard using a sector based approach.

static bool	findChessboardCornersSB (Mat image, in(double width, double height) patternSize, Mat corners, int flags)

static bool	findChessboardCornersSB (Mat image, in(double width, double height) patternSize, Mat corners)

static double double double double v3	estimateChessboardSharpnessAsValueTuple (Mat image, in(double width, double height) patternSize, Mat corners, float rise_distance, bool vertical, Mat sharpness)

static double double double double v3	estimateChessboardSharpnessAsValueTuple (Mat image, in(double width, double height) patternSize, Mat corners, float rise_distance, bool vertical)

static double double double double v3	estimateChessboardSharpnessAsValueTuple (Mat image, in(double width, double height) patternSize, Mat corners, float rise_distance)

static double double double double v3	estimateChessboardSharpnessAsValueTuple (Mat image, in(double width, double height) patternSize, Mat corners)

static bool	find4QuadCornerSubpix (Mat img, Mat corners, in(double width, double height) region_size)

static void	drawChessboardCorners (Mat image, in(double width, double height) patternSize, MatOfPoint2f corners, bool patternWasFound)
	Renders the detected chessboard corners.

static bool	findCirclesGrid (Mat image, in(double width, double height) patternSize, Mat centers, int flags)

static bool	findCirclesGrid (Mat image, in(double width, double height) patternSize, Mat centers)

static double	calibrateCameraExtended (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags, in(double type, double maxCount, double epsilon) criteria)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraExtended (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors, int flags)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraExtended (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat perViewErrors)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCamera (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, int flags, in(double type, double maxCount, double epsilon) criteria)

static double	calibrateCamera (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, int flags)

static double	calibrateCamera (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs)

static double	calibrateCameraROExtended (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors, int flags, in(double type, double maxCount, double epsilon) criteria)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraROExtended (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors, int flags)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraROExtended (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, Mat stdDeviationsIntrinsics, Mat stdDeviationsExtrinsics, Mat stdDeviationsObjPoints, Mat perViewErrors)
	Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

static double	calibrateCameraRO (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, int flags, in(double type, double maxCount, double epsilon) criteria)

static double	calibrateCameraRO (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints, int flags)

static double	calibrateCameraRO (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) imageSize, int iFixedPoint, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs, Mat newObjPoints)

static void	calibrationMatrixValues (Mat cameraMatrix, in(double width, double height) imageSize, double apertureWidth, double apertureHeight, double[] fovx, double[] fovy, double[] focalLength, out(double x, double y) principalPoint, double[] aspectRatio)
	Computes useful camera characteristics from the camera intrinsic matrix.

static double	stereoCalibrateExtended (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat E, Mat F, List< Mat > rvecs, List< Mat > tvecs, Mat perViewErrors, int flags, in(double type, double maxCount, double epsilon) criteria)
	Calibrates a stereo camera set up. This function finds the intrinsic parameters for each of the two cameras and the extrinsic parameters between the two cameras.

static double	stereoCalibrateExtended (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat E, Mat F, List< Mat > rvecs, List< Mat > tvecs, Mat perViewErrors, int flags)
	Calibrates a stereo camera set up. This function finds the intrinsic parameters for each of the two cameras and the extrinsic parameters between the two cameras.

static double	stereoCalibrateExtended (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat E, Mat F, List< Mat > rvecs, List< Mat > tvecs, Mat perViewErrors)
	Calibrates a stereo camera set up. This function finds the intrinsic parameters for each of the two cameras and the extrinsic parameters between the two cameras.

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat E, Mat F, int flags, in(double type, double maxCount, double epsilon) criteria)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat E, Mat F, int flags)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat E, Mat F)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors, int flags, in(double type, double maxCount, double epsilon) criteria)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors, int flags)

static double	stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat E, Mat F, Mat perViewErrors)

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, in(double width, double height) newImageSize, out(int x, int y, int width, int height) validPixROI1, out(int x, int y, int width, int height) validPixROI2)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, in(double width, double height) newImageSize, out(int x, int y, int width, int height) validPixROI1)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha, in(double width, double height) newImageSize)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, double alpha)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags)
	Computes rectification transforms for each head of a calibrated stereo camera.

static void	stereoRectify (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, in(double width, double height) imageSize, Mat R, Mat T, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q)
	Computes rectification transforms for each head of a calibrated stereo camera.

static bool	stereoRectifyUncalibrated (Mat points1, Mat points2, Mat F, in(double width, double height) imgSize, Mat H1, Mat H2, double threshold)
	Computes a rectification transform for an uncalibrated stereo camera.

static bool	stereoRectifyUncalibrated (Mat points1, Mat points2, Mat F, in(double width, double height) imgSize, Mat H1, Mat H2)
	Computes a rectification transform for an uncalibrated stereo camera.

static float	rectify3Collinear (Mat cameraMatrix1, Mat distCoeffs1, Mat cameraMatrix2, Mat distCoeffs2, Mat cameraMatrix3, Mat distCoeffs3, List< Mat > imgpt1, List< Mat > imgpt3, in(double width, double height) imageSize, Mat R12, Mat T12, Mat R13, Mat T13, Mat R1, Mat R2, Mat R3, Mat P1, Mat P2, Mat P3, Mat Q, double alpha, in(double width, double height) newImgSize, out(int x, int y, int width, int height) roi1, out(int x, int y, int width, int height) roi2, int flags)

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, in(double width, double height) imageSize, double alpha, in(double width, double height) newImgSize, out(int x, int y, int width, int height) validPixROI, bool centerPrincipalPoint)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, in(double width, double height) imageSize, double alpha, in(double width, double height) newImgSize, out(int x, int y, int width, int height) validPixROI)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, in(double width, double height) imageSize, double alpha, in(double width, double height) newImgSize)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static Mat	getOptimalNewCameraMatrix (Mat cameraMatrix, Mat distCoeffs, in(double width, double height) imageSize, double alpha)
	Returns the new camera intrinsic matrix based on the free scaling parameter.

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in(double x, double y) pp, int method, double prob, double threshold, int maxIters, Mat mask)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in(double x, double y) pp, int method, double prob, double threshold, int maxIters)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in(double x, double y) pp, int method, double prob, double threshold)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in(double x, double y) pp, int method, double prob)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in(double x, double y) pp, int method)

static Mat	findEssentialMat (Mat points1, Mat points2, double focal, in(double x, double y) pp)

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat R, Mat t, double focal, in(double x, double y) pp, Mat mask)

static int	recoverPose (Mat E, Mat points1, Mat points2, Mat R, Mat t, double focal, in(double x, double y) pp)

static int int int int height	getValidDisparityROIAsValueTuple (in(int x, int y, int width, int height) roi1,(int x, int y, int width, int height) roi2, int minDisparity, int numberOfDisparities, int blockSize)

static void	initUndistortRectifyMap (Mat cameraMatrix, Mat distCoeffs, Mat R, Mat newCameraMatrix, in(double width, double height) size, int m1type, Mat map1, Mat map2)
	Computes the undistortion and rectification transformation map.

static void	initInverseRectificationMap (Mat cameraMatrix, Mat distCoeffs, Mat R, Mat newCameraMatrix, in(double width, double height) size, int m1type, Mat map1, Mat map2)
	Computes the projection and inverse-rectification transformation map. In essense, this is the inverse of initUndistortRectifyMap to accomodate stereo-rectification of projectors ('inverse-cameras') in projector-camera pairs.

static Mat	getDefaultNewCameraMatrix (Mat cameraMatrix, in(double width, double height) imgsize, bool centerPrincipalPoint)
	Returns the default new camera matrix.

static Mat	getDefaultNewCameraMatrix (Mat cameraMatrix, in(double width, double height) imgsize)
	Returns the default new camera matrix.

static void	undistortPointsIter (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, Mat R, Mat P, in(double type, double maxCount, double epsilon) criteria)

static void	undistortImagePoints (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, in(double type, double maxCount, double epsilon) arg1)
	Compute undistorted image points position.

static void	fisheye_undistortPoints (Mat distorted, Mat undistorted, Mat K, Mat D, Mat R, Mat P, in(double type, double maxCount, double epsilon) criteria)
	Undistorts 2D points using fisheye model.

static void	fisheye_initUndistortRectifyMap (Mat K, Mat D, Mat R, Mat P, in(double width, double height) size, int m1type, Mat map1, Mat map2)
	Computes undistortion and rectification maps for image transform by #remap. If D is empty zero distortion is used, if R or P is empty identity matrixes are used.

static void	fisheye_undistortImage (Mat distorted, Mat undistorted, Mat K, Mat D, Mat Knew, in(double width, double height) new_size)
	Transforms an image to compensate for fisheye lens distortion.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, in(double width, double height) image_size, Mat R, Mat P, double balance, in(double width, double height) new_size, double fov_scale)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, in(double width, double height) image_size, Mat R, Mat P, double balance, in(double width, double height) new_size)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, in(double width, double height) image_size, Mat R, Mat P, double balance)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static void	fisheye_estimateNewCameraMatrixForUndistortRectify (Mat K, Mat D, in(double width, double height) image_size, Mat R, Mat P)
	Estimates new camera intrinsic matrix for undistortion or rectification.

static double	fisheye_calibrate (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) image_size, Mat K, Mat D, List< Mat > rvecs, List< Mat > tvecs, int flags, in(double type, double maxCount, double epsilon) criteria)
	Performs camera calibration.

static double	fisheye_calibrate (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) image_size, Mat K, Mat D, List< Mat > rvecs, List< Mat > tvecs, int flags)
	Performs camera calibration.

static double	fisheye_calibrate (List< Mat > objectPoints, List< Mat > imagePoints, in(double width, double height) image_size, Mat K, Mat D, List< Mat > rvecs, List< Mat > tvecs)
	Performs camera calibration.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, in(double width, double height) imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, in(double width, double height) newImageSize, double balance, double fov_scale)
	Stereo rectification for fisheye camera model.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, in(double width, double height) imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, in(double width, double height) newImageSize, double balance)
	Stereo rectification for fisheye camera model.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, in(double width, double height) imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags, in(double width, double height) newImageSize)
	Stereo rectification for fisheye camera model.

static void	fisheye_stereoRectify (Mat K1, Mat D1, Mat K2, Mat D2, in(double width, double height) imageSize, Mat R, Mat tvec, Mat R1, Mat R2, Mat P1, Mat P2, Mat Q, int flags)
	Stereo rectification for fisheye camera model.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in(double width, double height) imageSize, Mat R, Mat T, List< Mat > rvecs, List< Mat > tvecs, int flags, in(double type, double maxCount, double epsilon) criteria)
	Performs stereo calibration.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in(double width, double height) imageSize, Mat R, Mat T, List< Mat > rvecs, List< Mat > tvecs, int flags)
	Performs stereo calibration.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in(double width, double height) imageSize, Mat R, Mat T, List< Mat > rvecs, List< Mat > tvecs)
	Performs stereo calibration.

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in(double width, double height) imageSize, Mat R, Mat T, int flags, in(double type, double maxCount, double epsilon) criteria)

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in(double width, double height) imageSize, Mat R, Mat T, int flags)

static double	fisheye_stereoCalibrate (List< Mat > objectPoints, List< Mat > imagePoints1, List< Mat > imagePoints2, Mat K1, Mat D1, Mat K2, Mat D2, in(double width, double height) imageSize, Mat R, Mat T)

static bool	fisheye_solvePnP (Mat objectPoints, Mat imagePoints, Mat cameraMatrix, Mat distCoeffs, Mat rvec, Mat tvec, bool useExtrinsicGuess, int flags, in(double type, double maxCount, double epsilon) criteria)
	Finds an object pose from 3D-2D point correspondences for fisheye camera moodel.

Static Public Attributes
const int	CV_ITERATIVE = 0

const int	CV_EPNP = 1

const int	CV_P3P = 2

const int	CV_DLS = 3

const int	CvLevMarq_DONE = 0

const int	CvLevMarq_STARTED = 1

const int	CvLevMarq_CALC_J = 2

const int	CvLevMarq_CHECK_ERR = 3

const int	LMEDS = 4

const int	RANSAC = 8

const int	RHO = 16

const int	USAC_DEFAULT = 32

const int	USAC_PARALLEL = 33

const int	USAC_FM_8PTS = 34

const int	USAC_FAST = 35

const int	USAC_ACCURATE = 36

const int	USAC_PROSAC = 37

const int	USAC_MAGSAC = 38

const int	CALIB_CB_ADAPTIVE_THRESH = 1

const int	CALIB_CB_NORMALIZE_IMAGE = 2

const int	CALIB_CB_FILTER_QUADS = 4

const int	CALIB_CB_FAST_CHECK = 8

const int	CALIB_CB_EXHAUSTIVE = 16

const int	CALIB_CB_ACCURACY = 32

const int	CALIB_CB_LARGER = 64

const int	CALIB_CB_MARKER = 128

const int	CALIB_CB_PLAIN = 256

const int	CALIB_CB_SYMMETRIC_GRID = 1

const int	CALIB_CB_ASYMMETRIC_GRID = 2

const int	CALIB_CB_CLUSTERING = 4

const int	CALIB_NINTRINSIC = 18

const int	CALIB_USE_INTRINSIC_GUESS = 0x00001

const int	CALIB_FIX_ASPECT_RATIO = 0x00002

const int	CALIB_FIX_PRINCIPAL_POINT = 0x00004

const int	CALIB_ZERO_TANGENT_DIST = 0x00008

const int	CALIB_FIX_FOCAL_LENGTH = 0x00010

const int	CALIB_FIX_K1 = 0x00020

const int	CALIB_FIX_K2 = 0x00040

const int	CALIB_FIX_K3 = 0x00080

const int	CALIB_FIX_K4 = 0x00800

const int	CALIB_FIX_K5 = 0x01000

const int	CALIB_FIX_K6 = 0x02000

const int	CALIB_RATIONAL_MODEL = 0x04000

const int	CALIB_THIN_PRISM_MODEL = 0x08000

const int	CALIB_FIX_S1_S2_S3_S4 = 0x10000

const int	CALIB_TILTED_MODEL = 0x40000

const int	CALIB_FIX_TAUX_TAUY = 0x80000

const int	CALIB_USE_QR = 0x100000

const int	CALIB_FIX_TANGENT_DIST = 0x200000

const int	CALIB_FIX_INTRINSIC = 0x00100

const int	CALIB_SAME_FOCAL_LENGTH = 0x00200

const int	CALIB_ZERO_DISPARITY = 0x00400

const int	CALIB_USE_LU = (1 << 17)

const int	CALIB_USE_EXTRINSIC_GUESS = (1 << 22)

const int	FM_7POINT = 1

const int	FM_8POINT = 2

const int	FM_LMEDS = 4

const int	FM_RANSAC = 8

const int	fisheye_CALIB_USE_INTRINSIC_GUESS = 1 << 0

const int	fisheye_CALIB_RECOMPUTE_EXTRINSIC = 1 << 1

const int	fisheye_CALIB_CHECK_COND = 1 << 2

const int	fisheye_CALIB_FIX_SKEW = 1 << 3

const int	fisheye_CALIB_FIX_K1 = 1 << 4

const int	fisheye_CALIB_FIX_K2 = 1 << 5

const int	fisheye_CALIB_FIX_K3 = 1 << 6

const int	fisheye_CALIB_FIX_K4 = 1 << 7

const int	fisheye_CALIB_FIX_INTRINSIC = 1 << 8

const int	fisheye_CALIB_FIX_PRINCIPAL_POINT = 1 << 9

const int	fisheye_CALIB_ZERO_DISPARITY = 1 << 10

const int	fisheye_CALIB_FIX_FOCAL_LENGTH = 1 << 11

const int	CirclesGridFinderParameters_SYMMETRIC_GRID = 0

const int	CirclesGridFinderParameters_ASYMMETRIC_GRID = 1

const int	CALIB_HAND_EYE_TSAI = 0

const int	CALIB_HAND_EYE_PARK = 1

const int	CALIB_HAND_EYE_HORAUD = 2

const int	CALIB_HAND_EYE_ANDREFF = 3

const int	CALIB_HAND_EYE_DANIILIDIS = 4

const int	LOCAL_OPTIM_NULL = 0

const int	LOCAL_OPTIM_INNER_LO = 1

const int	LOCAL_OPTIM_INNER_AND_ITER_LO = 2

const int	LOCAL_OPTIM_GC = 3

const int	LOCAL_OPTIM_SIGMA = 4

const int	NEIGH_FLANN_KNN = 0

const int	NEIGH_GRID = 1

const int	NEIGH_FLANN_RADIUS = 2

const int	NONE_POLISHER = 0

const int	LSQ_POLISHER = 1

const int	MAGSAC = 2

const int	COV_POLISHER = 3

const int	CALIB_ROBOT_WORLD_HAND_EYE_SHAH = 0

const int	CALIB_ROBOT_WORLD_HAND_EYE_LI = 1

const int	SAMPLING_UNIFORM = 0

const int	SAMPLING_PROGRESSIVE_NAPSAC = 1

const int	SAMPLING_NAPSAC = 2

const int	SAMPLING_PROSAC = 3

const int	SCORE_METHOD_RANSAC = 0

const int	SCORE_METHOD_MSAC = 1

const int	SCORE_METHOD_MAGSAC = 2

const int	SCORE_METHOD_LMEDS = 3

const int	SOLVEPNP_ITERATIVE = 0

const int	SOLVEPNP_EPNP = 1

const int	SOLVEPNP_P3P = 2

const int	SOLVEPNP_DLS = 3

const int	SOLVEPNP_UPNP = 4

const int	SOLVEPNP_AP3P = 5

const int	SOLVEPNP_IPPE = 6

const int	SOLVEPNP_IPPE_SQUARE = 7

const int	SOLVEPNP_SQPNP = 8

const int	SOLVEPNP_MAX_COUNT = 8 + 1

const int	PROJ_SPHERICAL_ORTHO = 0

const int	PROJ_SPHERICAL_EQRECT = 1

static double	v0
	Estimates the sharpness of a detected chessboard.

static double double	v1

static double double double	v2

static int	x

static int int	y

static int int int	width

Member Function Documentation

◆ calibrateCamera() [1/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCamera	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCamera() [2/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCamera	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		int	flags )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCamera() [3/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCamera	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		int	flags,
		in Vec3d	criteria )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCamera() [4/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCamera	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCamera() [5/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCamera	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		int	flags )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCamera() [6/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCamera	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		int	flags,
		in(double type, double maxCount, double epsilon)	criteria )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCamera() [7/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCamera	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCamera() [8/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCamera	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		int	flags )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCamera() [9/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCamera	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		int	flags,
		TermCriteria	criteria )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCameraExtended() [1/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	perViewErrors )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

Parameters

objectPoints	In the new interface it is a vector of vectors of calibration pattern points in the calibration pattern coordinate space (e.g. std::vector<std::vector<cv::Vec3f>>). The outer vector contains as many elements as the number of pattern views. If the same calibration pattern is shown in each view and it is fully visible, all the vectors will be the same. Although, it is possible to use partially occluded patterns or even different patterns in different views. Then, the vectors will be different. Although the points are 3D, they all lie in the calibration pattern's XY coordinate plane (thus 0 in the Z-coordinate), if the used calibration pattern is a planar rig. In the old interface all the vectors of object points from different views are concatenated together.
imagePoints	In the new interface it is a vector of vectors of the projections of calibration pattern points (e.g. std::vector<std::vector<cv::Vec2f>>). imagePoints.size() and objectPoints.size(), and imagePoints[i].size() and objectPoints[i].size() for each i, must be equal, respectively. In the old interface all the vectors of object points from different views are concatenated together.
imageSize	Size of the image used only to initialize the camera intrinsic matrix.
cameraMatrix	Input/output 3x3 floating-point camera intrinsic matrix \(\cameramatrix{A}\) . If CALIB_USE_INTRINSIC_GUESS and/or CALIB_FIX_ASPECT_RATIO, CALIB_FIX_PRINCIPAL_POINT or CALIB_FIX_FOCAL_LENGTH are specified, some or all of fx, fy, cx, cy must be initialized before calling the function.
distCoeffs	Input/output vector of distortion coefficients \(\distcoeffs\).
rvecs	Output vector of rotation vectors (Rodrigues ) estimated for each pattern view (e.g. std::vector<cv::Mat>>). That is, each i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter description) brings the calibration pattern from the object coordinate space (in which object points are specified) to the camera coordinate space. In more technical terms, the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space to camera coordinate space. Due to its duality, this tuple is equivalent to the position of the calibration pattern with respect to the camera coordinate space.
tvecs	Output vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. Order of deviations values: \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. Order of deviations values: \((R_0, T_0, \dotsc , R_{M - 1}, T_{M - 1})\) where M is the number of pattern views. \(R_i, T_i\) are concatenated 1x3 vectors.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of the following values: CALIB_USE_INTRINSIC_GUESS cameraMatrix contains valid initial values of fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image center ( imageSize is used), and focal distances are computed in a least-squares fashion. Note, that if intrinsic parameters are known, there is no need to use this function just to estimate extrinsic parameters. Use solvePnP instead. CALIB_FIX_PRINCIPAL_POINT The principal point is not changed during the global optimization. It stays at the center or at a different location specified when CALIB_USE_INTRINSIC_GUESS is set too. CALIB_FIX_ASPECT_RATIO The functions consider only fy as a free parameter. The ratio fx/fy stays the same as in the input cameraMatrix . When CALIB_USE_INTRINSIC_GUESS is not set, the actual input values of fx and fy are ignored, only their ratio is computed and used further. CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients \((p_1, p_2)\) are set to zeros and stay zero. CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global optimization if CALIB_USE_INTRINSIC_GUESS is set. CALIB_FIX_K1,..., CALIB_FIX_K6 The corresponding radial distortion coefficient is not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_RATIONAL_MODEL Coefficients k4, k5, and k6 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the rational model and return 8 coefficients or more. CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the thin prism model and return 12 coefficients or more. CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the tilted sensor model and return 14 coefficients. CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000] and [BouguetMCT] . The coordinates of 3D object points and their corresponding 2D projections in each view must be specified. That may be achieved by using an object with known geometry and easily detectable feature points. Such an object is called a calibration rig or calibration pattern, and OpenCV has built-in support for a chessboard as a calibration rig (see findChessboardCorners). Currently, initialization of intrinsic parameters (when CALIB_USE_INTRINSIC_GUESS is not set) is only implemented for planar calibration patterns (where Z-coordinates of the object points must be all zeros). 3D calibration rigs can also be used as long as initial cameraMatrix is provided.

The algorithm performs the following steps:

Compute the initial intrinsic parameters (the option only available for planar calibration patterns) or read them from the input parameters. The distortion coefficients are all set to zeros initially unless some of CALIB_FIX_K? are specified.
Estimate the initial camera pose as if the intrinsic parameters have been already known. This is done using solvePnP .
Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error, that is, the total sum of squared distances between the observed feature points imagePoints and the projected (using the current estimates for camera parameters and the poses) object points objectPoints. See projectPoints for details.

Note: If you use a non-square (i.e. non-N-by-N) grid and findChessboardCorners for calibration, and calibrateCamera returns bad values (zero distortion coefficients, \(c_x\) and \(c_y\) very far from the image center, and/or large differences between \(f_x\) and \(f_y\) (ratios of 10:1 or more)), then you are probably using patternSize=cvSize(rows,cols) instead of using patternSize=cvSize(cols,rows) in findChessboardCorners.; The function may throw exceptions, if unsupported combination of parameters is provided or the system is underconstrained.

See also: calibrateCameraRO, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraExtended() [2/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	perViewErrors,
		int	flags )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

Parameters

objectPoints	In the new interface it is a vector of vectors of calibration pattern points in the calibration pattern coordinate space (e.g. std::vector<std::vector<cv::Vec3f>>). The outer vector contains as many elements as the number of pattern views. If the same calibration pattern is shown in each view and it is fully visible, all the vectors will be the same. Although, it is possible to use partially occluded patterns or even different patterns in different views. Then, the vectors will be different. Although the points are 3D, they all lie in the calibration pattern's XY coordinate plane (thus 0 in the Z-coordinate), if the used calibration pattern is a planar rig. In the old interface all the vectors of object points from different views are concatenated together.
imagePoints	In the new interface it is a vector of vectors of the projections of calibration pattern points (e.g. std::vector<std::vector<cv::Vec2f>>). imagePoints.size() and objectPoints.size(), and imagePoints[i].size() and objectPoints[i].size() for each i, must be equal, respectively. In the old interface all the vectors of object points from different views are concatenated together.
imageSize	Size of the image used only to initialize the camera intrinsic matrix.
cameraMatrix	Input/output 3x3 floating-point camera intrinsic matrix \(\cameramatrix{A}\) . If CALIB_USE_INTRINSIC_GUESS and/or CALIB_FIX_ASPECT_RATIO, CALIB_FIX_PRINCIPAL_POINT or CALIB_FIX_FOCAL_LENGTH are specified, some or all of fx, fy, cx, cy must be initialized before calling the function.
distCoeffs	Input/output vector of distortion coefficients \(\distcoeffs\).
rvecs	Output vector of rotation vectors (Rodrigues ) estimated for each pattern view (e.g. std::vector<cv::Mat>>). That is, each i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter description) brings the calibration pattern from the object coordinate space (in which object points are specified) to the camera coordinate space. In more technical terms, the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space to camera coordinate space. Due to its duality, this tuple is equivalent to the position of the calibration pattern with respect to the camera coordinate space.
tvecs	Output vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. Order of deviations values: \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. Order of deviations values: \((R_0, T_0, \dotsc , R_{M - 1}, T_{M - 1})\) where M is the number of pattern views. \(R_i, T_i\) are concatenated 1x3 vectors.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of the following values: CALIB_USE_INTRINSIC_GUESS cameraMatrix contains valid initial values of fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image center ( imageSize is used), and focal distances are computed in a least-squares fashion. Note, that if intrinsic parameters are known, there is no need to use this function just to estimate extrinsic parameters. Use solvePnP instead. CALIB_FIX_PRINCIPAL_POINT The principal point is not changed during the global optimization. It stays at the center or at a different location specified when CALIB_USE_INTRINSIC_GUESS is set too. CALIB_FIX_ASPECT_RATIO The functions consider only fy as a free parameter. The ratio fx/fy stays the same as in the input cameraMatrix . When CALIB_USE_INTRINSIC_GUESS is not set, the actual input values of fx and fy are ignored, only their ratio is computed and used further. CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients \((p_1, p_2)\) are set to zeros and stay zero. CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global optimization if CALIB_USE_INTRINSIC_GUESS is set. CALIB_FIX_K1,..., CALIB_FIX_K6 The corresponding radial distortion coefficient is not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_RATIONAL_MODEL Coefficients k4, k5, and k6 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the rational model and return 8 coefficients or more. CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the thin prism model and return 12 coefficients or more. CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the tilted sensor model and return 14 coefficients. CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000] and [BouguetMCT] . The coordinates of 3D object points and their corresponding 2D projections in each view must be specified. That may be achieved by using an object with known geometry and easily detectable feature points. Such an object is called a calibration rig or calibration pattern, and OpenCV has built-in support for a chessboard as a calibration rig (see findChessboardCorners). Currently, initialization of intrinsic parameters (when CALIB_USE_INTRINSIC_GUESS is not set) is only implemented for planar calibration patterns (where Z-coordinates of the object points must be all zeros). 3D calibration rigs can also be used as long as initial cameraMatrix is provided.

The algorithm performs the following steps:

Compute the initial intrinsic parameters (the option only available for planar calibration patterns) or read them from the input parameters. The distortion coefficients are all set to zeros initially unless some of CALIB_FIX_K? are specified.
Estimate the initial camera pose as if the intrinsic parameters have been already known. This is done using solvePnP .
Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error, that is, the total sum of squared distances between the observed feature points imagePoints and the projected (using the current estimates for camera parameters and the poses) object points objectPoints. See projectPoints for details.

Note: If you use a non-square (i.e. non-N-by-N) grid and findChessboardCorners for calibration, and calibrateCamera returns bad values (zero distortion coefficients, \(c_x\) and \(c_y\) very far from the image center, and/or large differences between \(f_x\) and \(f_y\) (ratios of 10:1 or more)), then you are probably using patternSize=cvSize(rows,cols) instead of using patternSize=cvSize(cols,rows) in findChessboardCorners.; The function may throw exceptions, if unsupported combination of parameters is provided or the system is underconstrained.

See also: calibrateCameraRO, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraExtended() [3/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	perViewErrors,
		int	flags,
		in Vec3d	criteria )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

Parameters

objectPoints	In the new interface it is a vector of vectors of calibration pattern points in the calibration pattern coordinate space (e.g. std::vector<std::vector<cv::Vec3f>>). The outer vector contains as many elements as the number of pattern views. If the same calibration pattern is shown in each view and it is fully visible, all the vectors will be the same. Although, it is possible to use partially occluded patterns or even different patterns in different views. Then, the vectors will be different. Although the points are 3D, they all lie in the calibration pattern's XY coordinate plane (thus 0 in the Z-coordinate), if the used calibration pattern is a planar rig. In the old interface all the vectors of object points from different views are concatenated together.
imagePoints	In the new interface it is a vector of vectors of the projections of calibration pattern points (e.g. std::vector<std::vector<cv::Vec2f>>). imagePoints.size() and objectPoints.size(), and imagePoints[i].size() and objectPoints[i].size() for each i, must be equal, respectively. In the old interface all the vectors of object points from different views are concatenated together.
imageSize	Size of the image used only to initialize the camera intrinsic matrix.
cameraMatrix	Input/output 3x3 floating-point camera intrinsic matrix \(\cameramatrix{A}\) . If CALIB_USE_INTRINSIC_GUESS and/or CALIB_FIX_ASPECT_RATIO, CALIB_FIX_PRINCIPAL_POINT or CALIB_FIX_FOCAL_LENGTH are specified, some or all of fx, fy, cx, cy must be initialized before calling the function.
distCoeffs	Input/output vector of distortion coefficients \(\distcoeffs\).
rvecs	Output vector of rotation vectors (Rodrigues ) estimated for each pattern view (e.g. std::vector<cv::Mat>>). That is, each i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter description) brings the calibration pattern from the object coordinate space (in which object points are specified) to the camera coordinate space. In more technical terms, the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space to camera coordinate space. Due to its duality, this tuple is equivalent to the position of the calibration pattern with respect to the camera coordinate space.
tvecs	Output vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. Order of deviations values: \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. Order of deviations values: \((R_0, T_0, \dotsc , R_{M - 1}, T_{M - 1})\) where M is the number of pattern views. \(R_i, T_i\) are concatenated 1x3 vectors.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of the following values: CALIB_USE_INTRINSIC_GUESS cameraMatrix contains valid initial values of fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image center ( imageSize is used), and focal distances are computed in a least-squares fashion. Note, that if intrinsic parameters are known, there is no need to use this function just to estimate extrinsic parameters. Use solvePnP instead. CALIB_FIX_PRINCIPAL_POINT The principal point is not changed during the global optimization. It stays at the center or at a different location specified when CALIB_USE_INTRINSIC_GUESS is set too. CALIB_FIX_ASPECT_RATIO The functions consider only fy as a free parameter. The ratio fx/fy stays the same as in the input cameraMatrix . When CALIB_USE_INTRINSIC_GUESS is not set, the actual input values of fx and fy are ignored, only their ratio is computed and used further. CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients \((p_1, p_2)\) are set to zeros and stay zero. CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global optimization if CALIB_USE_INTRINSIC_GUESS is set. CALIB_FIX_K1,..., CALIB_FIX_K6 The corresponding radial distortion coefficient is not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_RATIONAL_MODEL Coefficients k4, k5, and k6 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the rational model and return 8 coefficients or more. CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the thin prism model and return 12 coefficients or more. CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the tilted sensor model and return 14 coefficients. CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000] and [BouguetMCT] . The coordinates of 3D object points and their corresponding 2D projections in each view must be specified. That may be achieved by using an object with known geometry and easily detectable feature points. Such an object is called a calibration rig or calibration pattern, and OpenCV has built-in support for a chessboard as a calibration rig (see findChessboardCorners). Currently, initialization of intrinsic parameters (when CALIB_USE_INTRINSIC_GUESS is not set) is only implemented for planar calibration patterns (where Z-coordinates of the object points must be all zeros). 3D calibration rigs can also be used as long as initial cameraMatrix is provided.

The algorithm performs the following steps:

Compute the initial intrinsic parameters (the option only available for planar calibration patterns) or read them from the input parameters. The distortion coefficients are all set to zeros initially unless some of CALIB_FIX_K? are specified.
Estimate the initial camera pose as if the intrinsic parameters have been already known. This is done using solvePnP .
Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error, that is, the total sum of squared distances between the observed feature points imagePoints and the projected (using the current estimates for camera parameters and the poses) object points objectPoints. See projectPoints for details.

Note: If you use a non-square (i.e. non-N-by-N) grid and findChessboardCorners for calibration, and calibrateCamera returns bad values (zero distortion coefficients, \(c_x\) and \(c_y\) very far from the image center, and/or large differences between \(f_x\) and \(f_y\) (ratios of 10:1 or more)), then you are probably using patternSize=cvSize(rows,cols) instead of using patternSize=cvSize(cols,rows) in findChessboardCorners.; The function may throw exceptions, if unsupported combination of parameters is provided or the system is underconstrained.

See also: calibrateCameraRO, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraExtended() [4/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	perViewErrors )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

Parameters

objectPoints	In the new interface it is a vector of vectors of calibration pattern points in the calibration pattern coordinate space (e.g. std::vector<std::vector<cv::Vec3f>>). The outer vector contains as many elements as the number of pattern views. If the same calibration pattern is shown in each view and it is fully visible, all the vectors will be the same. Although, it is possible to use partially occluded patterns or even different patterns in different views. Then, the vectors will be different. Although the points are 3D, they all lie in the calibration pattern's XY coordinate plane (thus 0 in the Z-coordinate), if the used calibration pattern is a planar rig. In the old interface all the vectors of object points from different views are concatenated together.
imagePoints	In the new interface it is a vector of vectors of the projections of calibration pattern points (e.g. std::vector<std::vector<cv::Vec2f>>). imagePoints.size() and objectPoints.size(), and imagePoints[i].size() and objectPoints[i].size() for each i, must be equal, respectively. In the old interface all the vectors of object points from different views are concatenated together.
imageSize	Size of the image used only to initialize the camera intrinsic matrix.
cameraMatrix	Input/output 3x3 floating-point camera intrinsic matrix \(\cameramatrix{A}\) . If CALIB_USE_INTRINSIC_GUESS and/or CALIB_FIX_ASPECT_RATIO, CALIB_FIX_PRINCIPAL_POINT or CALIB_FIX_FOCAL_LENGTH are specified, some or all of fx, fy, cx, cy must be initialized before calling the function.
distCoeffs	Input/output vector of distortion coefficients \(\distcoeffs\).
rvecs	Output vector of rotation vectors (Rodrigues ) estimated for each pattern view (e.g. std::vector<cv::Mat>>). That is, each i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter description) brings the calibration pattern from the object coordinate space (in which object points are specified) to the camera coordinate space. In more technical terms, the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space to camera coordinate space. Due to its duality, this tuple is equivalent to the position of the calibration pattern with respect to the camera coordinate space.
tvecs	Output vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. Order of deviations values: \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. Order of deviations values: \((R_0, T_0, \dotsc , R_{M - 1}, T_{M - 1})\) where M is the number of pattern views. \(R_i, T_i\) are concatenated 1x3 vectors.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of the following values: CALIB_USE_INTRINSIC_GUESS cameraMatrix contains valid initial values of fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image center ( imageSize is used), and focal distances are computed in a least-squares fashion. Note, that if intrinsic parameters are known, there is no need to use this function just to estimate extrinsic parameters. Use solvePnP instead. CALIB_FIX_PRINCIPAL_POINT The principal point is not changed during the global optimization. It stays at the center or at a different location specified when CALIB_USE_INTRINSIC_GUESS is set too. CALIB_FIX_ASPECT_RATIO The functions consider only fy as a free parameter. The ratio fx/fy stays the same as in the input cameraMatrix . When CALIB_USE_INTRINSIC_GUESS is not set, the actual input values of fx and fy are ignored, only their ratio is computed and used further. CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients \((p_1, p_2)\) are set to zeros and stay zero. CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global optimization if CALIB_USE_INTRINSIC_GUESS is set. CALIB_FIX_K1,..., CALIB_FIX_K6 The corresponding radial distortion coefficient is not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_RATIONAL_MODEL Coefficients k4, k5, and k6 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the rational model and return 8 coefficients or more. CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the thin prism model and return 12 coefficients or more. CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the tilted sensor model and return 14 coefficients. CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000] and [BouguetMCT] . The coordinates of 3D object points and their corresponding 2D projections in each view must be specified. That may be achieved by using an object with known geometry and easily detectable feature points. Such an object is called a calibration rig or calibration pattern, and OpenCV has built-in support for a chessboard as a calibration rig (see findChessboardCorners). Currently, initialization of intrinsic parameters (when CALIB_USE_INTRINSIC_GUESS is not set) is only implemented for planar calibration patterns (where Z-coordinates of the object points must be all zeros). 3D calibration rigs can also be used as long as initial cameraMatrix is provided.

The algorithm performs the following steps:

Compute the initial intrinsic parameters (the option only available for planar calibration patterns) or read them from the input parameters. The distortion coefficients are all set to zeros initially unless some of CALIB_FIX_K? are specified.
Estimate the initial camera pose as if the intrinsic parameters have been already known. This is done using solvePnP .
Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error, that is, the total sum of squared distances between the observed feature points imagePoints and the projected (using the current estimates for camera parameters and the poses) object points objectPoints. See projectPoints for details.

Note: If you use a non-square (i.e. non-N-by-N) grid and findChessboardCorners for calibration, and calibrateCamera returns bad values (zero distortion coefficients, \(c_x\) and \(c_y\) very far from the image center, and/or large differences between \(f_x\) and \(f_y\) (ratios of 10:1 or more)), then you are probably using patternSize=cvSize(rows,cols) instead of using patternSize=cvSize(cols,rows) in findChessboardCorners.; The function may throw exceptions, if unsupported combination of parameters is provided or the system is underconstrained.

See also: calibrateCameraRO, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraExtended() [5/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	perViewErrors,
		int	flags )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

Parameters

objectPoints	In the new interface it is a vector of vectors of calibration pattern points in the calibration pattern coordinate space (e.g. std::vector<std::vector<cv::Vec3f>>). The outer vector contains as many elements as the number of pattern views. If the same calibration pattern is shown in each view and it is fully visible, all the vectors will be the same. Although, it is possible to use partially occluded patterns or even different patterns in different views. Then, the vectors will be different. Although the points are 3D, they all lie in the calibration pattern's XY coordinate plane (thus 0 in the Z-coordinate), if the used calibration pattern is a planar rig. In the old interface all the vectors of object points from different views are concatenated together.
imagePoints	In the new interface it is a vector of vectors of the projections of calibration pattern points (e.g. std::vector<std::vector<cv::Vec2f>>). imagePoints.size() and objectPoints.size(), and imagePoints[i].size() and objectPoints[i].size() for each i, must be equal, respectively. In the old interface all the vectors of object points from different views are concatenated together.
imageSize	Size of the image used only to initialize the camera intrinsic matrix.
cameraMatrix	Input/output 3x3 floating-point camera intrinsic matrix \(\cameramatrix{A}\) . If CALIB_USE_INTRINSIC_GUESS and/or CALIB_FIX_ASPECT_RATIO, CALIB_FIX_PRINCIPAL_POINT or CALIB_FIX_FOCAL_LENGTH are specified, some or all of fx, fy, cx, cy must be initialized before calling the function.
distCoeffs	Input/output vector of distortion coefficients \(\distcoeffs\).
rvecs	Output vector of rotation vectors (Rodrigues ) estimated for each pattern view (e.g. std::vector<cv::Mat>>). That is, each i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter description) brings the calibration pattern from the object coordinate space (in which object points are specified) to the camera coordinate space. In more technical terms, the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space to camera coordinate space. Due to its duality, this tuple is equivalent to the position of the calibration pattern with respect to the camera coordinate space.
tvecs	Output vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. Order of deviations values: \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. Order of deviations values: \((R_0, T_0, \dotsc , R_{M - 1}, T_{M - 1})\) where M is the number of pattern views. \(R_i, T_i\) are concatenated 1x3 vectors.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of the following values: CALIB_USE_INTRINSIC_GUESS cameraMatrix contains valid initial values of fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image center ( imageSize is used), and focal distances are computed in a least-squares fashion. Note, that if intrinsic parameters are known, there is no need to use this function just to estimate extrinsic parameters. Use solvePnP instead. CALIB_FIX_PRINCIPAL_POINT The principal point is not changed during the global optimization. It stays at the center or at a different location specified when CALIB_USE_INTRINSIC_GUESS is set too. CALIB_FIX_ASPECT_RATIO The functions consider only fy as a free parameter. The ratio fx/fy stays the same as in the input cameraMatrix . When CALIB_USE_INTRINSIC_GUESS is not set, the actual input values of fx and fy are ignored, only their ratio is computed and used further. CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients \((p_1, p_2)\) are set to zeros and stay zero. CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global optimization if CALIB_USE_INTRINSIC_GUESS is set. CALIB_FIX_K1,..., CALIB_FIX_K6 The corresponding radial distortion coefficient is not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_RATIONAL_MODEL Coefficients k4, k5, and k6 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the rational model and return 8 coefficients or more. CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the thin prism model and return 12 coefficients or more. CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the tilted sensor model and return 14 coefficients. CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000] and [BouguetMCT] . The coordinates of 3D object points and their corresponding 2D projections in each view must be specified. That may be achieved by using an object with known geometry and easily detectable feature points. Such an object is called a calibration rig or calibration pattern, and OpenCV has built-in support for a chessboard as a calibration rig (see findChessboardCorners). Currently, initialization of intrinsic parameters (when CALIB_USE_INTRINSIC_GUESS is not set) is only implemented for planar calibration patterns (where Z-coordinates of the object points must be all zeros). 3D calibration rigs can also be used as long as initial cameraMatrix is provided.

The algorithm performs the following steps:

Compute the initial intrinsic parameters (the option only available for planar calibration patterns) or read them from the input parameters. The distortion coefficients are all set to zeros initially unless some of CALIB_FIX_K? are specified.
Estimate the initial camera pose as if the intrinsic parameters have been already known. This is done using solvePnP .
Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error, that is, the total sum of squared distances between the observed feature points imagePoints and the projected (using the current estimates for camera parameters and the poses) object points objectPoints. See projectPoints for details.

Note: If you use a non-square (i.e. non-N-by-N) grid and findChessboardCorners for calibration, and calibrateCamera returns bad values (zero distortion coefficients, \(c_x\) and \(c_y\) very far from the image center, and/or large differences between \(f_x\) and \(f_y\) (ratios of 10:1 or more)), then you are probably using patternSize=cvSize(rows,cols) instead of using patternSize=cvSize(cols,rows) in findChessboardCorners.; The function may throw exceptions, if unsupported combination of parameters is provided or the system is underconstrained.

See also: calibrateCameraRO, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraExtended() [6/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	perViewErrors,
		int	flags,
		in(double type, double maxCount, double epsilon)	criteria )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

Parameters

objectPoints	In the new interface it is a vector of vectors of calibration pattern points in the calibration pattern coordinate space (e.g. std::vector<std::vector<cv::Vec3f>>). The outer vector contains as many elements as the number of pattern views. If the same calibration pattern is shown in each view and it is fully visible, all the vectors will be the same. Although, it is possible to use partially occluded patterns or even different patterns in different views. Then, the vectors will be different. Although the points are 3D, they all lie in the calibration pattern's XY coordinate plane (thus 0 in the Z-coordinate), if the used calibration pattern is a planar rig. In the old interface all the vectors of object points from different views are concatenated together.
imagePoints	In the new interface it is a vector of vectors of the projections of calibration pattern points (e.g. std::vector<std::vector<cv::Vec2f>>). imagePoints.size() and objectPoints.size(), and imagePoints[i].size() and objectPoints[i].size() for each i, must be equal, respectively. In the old interface all the vectors of object points from different views are concatenated together.
imageSize	Size of the image used only to initialize the camera intrinsic matrix.
cameraMatrix	Input/output 3x3 floating-point camera intrinsic matrix \(\cameramatrix{A}\) . If CALIB_USE_INTRINSIC_GUESS and/or CALIB_FIX_ASPECT_RATIO, CALIB_FIX_PRINCIPAL_POINT or CALIB_FIX_FOCAL_LENGTH are specified, some or all of fx, fy, cx, cy must be initialized before calling the function.
distCoeffs	Input/output vector of distortion coefficients \(\distcoeffs\).
rvecs	Output vector of rotation vectors (Rodrigues ) estimated for each pattern view (e.g. std::vector<cv::Mat>>). That is, each i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter description) brings the calibration pattern from the object coordinate space (in which object points are specified) to the camera coordinate space. In more technical terms, the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space to camera coordinate space. Due to its duality, this tuple is equivalent to the position of the calibration pattern with respect to the camera coordinate space.
tvecs	Output vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. Order of deviations values: \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. Order of deviations values: \((R_0, T_0, \dotsc , R_{M - 1}, T_{M - 1})\) where M is the number of pattern views. \(R_i, T_i\) are concatenated 1x3 vectors.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of the following values: CALIB_USE_INTRINSIC_GUESS cameraMatrix contains valid initial values of fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image center ( imageSize is used), and focal distances are computed in a least-squares fashion. Note, that if intrinsic parameters are known, there is no need to use this function just to estimate extrinsic parameters. Use solvePnP instead. CALIB_FIX_PRINCIPAL_POINT The principal point is not changed during the global optimization. It stays at the center or at a different location specified when CALIB_USE_INTRINSIC_GUESS is set too. CALIB_FIX_ASPECT_RATIO The functions consider only fy as a free parameter. The ratio fx/fy stays the same as in the input cameraMatrix . When CALIB_USE_INTRINSIC_GUESS is not set, the actual input values of fx and fy are ignored, only their ratio is computed and used further. CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients \((p_1, p_2)\) are set to zeros and stay zero. CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global optimization if CALIB_USE_INTRINSIC_GUESS is set. CALIB_FIX_K1,..., CALIB_FIX_K6 The corresponding radial distortion coefficient is not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_RATIONAL_MODEL Coefficients k4, k5, and k6 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the rational model and return 8 coefficients or more. CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the thin prism model and return 12 coefficients or more. CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the tilted sensor model and return 14 coefficients. CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000] and [BouguetMCT] . The coordinates of 3D object points and their corresponding 2D projections in each view must be specified. That may be achieved by using an object with known geometry and easily detectable feature points. Such an object is called a calibration rig or calibration pattern, and OpenCV has built-in support for a chessboard as a calibration rig (see findChessboardCorners). Currently, initialization of intrinsic parameters (when CALIB_USE_INTRINSIC_GUESS is not set) is only implemented for planar calibration patterns (where Z-coordinates of the object points must be all zeros). 3D calibration rigs can also be used as long as initial cameraMatrix is provided.

The algorithm performs the following steps:

Compute the initial intrinsic parameters (the option only available for planar calibration patterns) or read them from the input parameters. The distortion coefficients are all set to zeros initially unless some of CALIB_FIX_K? are specified.
Estimate the initial camera pose as if the intrinsic parameters have been already known. This is done using solvePnP .
Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error, that is, the total sum of squared distances between the observed feature points imagePoints and the projected (using the current estimates for camera parameters and the poses) object points objectPoints. See projectPoints for details.

Note: If you use a non-square (i.e. non-N-by-N) grid and findChessboardCorners for calibration, and calibrateCamera returns bad values (zero distortion coefficients, \(c_x\) and \(c_y\) very far from the image center, and/or large differences between \(f_x\) and \(f_y\) (ratios of 10:1 or more)), then you are probably using patternSize=cvSize(rows,cols) instead of using patternSize=cvSize(cols,rows) in findChessboardCorners.; The function may throw exceptions, if unsupported combination of parameters is provided or the system is underconstrained.

See also: calibrateCameraRO, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraExtended() [7/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	perViewErrors )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

Parameters

objectPoints	In the new interface it is a vector of vectors of calibration pattern points in the calibration pattern coordinate space (e.g. std::vector<std::vector<cv::Vec3f>>). The outer vector contains as many elements as the number of pattern views. If the same calibration pattern is shown in each view and it is fully visible, all the vectors will be the same. Although, it is possible to use partially occluded patterns or even different patterns in different views. Then, the vectors will be different. Although the points are 3D, they all lie in the calibration pattern's XY coordinate plane (thus 0 in the Z-coordinate), if the used calibration pattern is a planar rig. In the old interface all the vectors of object points from different views are concatenated together.
imagePoints	In the new interface it is a vector of vectors of the projections of calibration pattern points (e.g. std::vector<std::vector<cv::Vec2f>>). imagePoints.size() and objectPoints.size(), and imagePoints[i].size() and objectPoints[i].size() for each i, must be equal, respectively. In the old interface all the vectors of object points from different views are concatenated together.
imageSize	Size of the image used only to initialize the camera intrinsic matrix.
cameraMatrix	Input/output 3x3 floating-point camera intrinsic matrix \(\cameramatrix{A}\) . If CALIB_USE_INTRINSIC_GUESS and/or CALIB_FIX_ASPECT_RATIO, CALIB_FIX_PRINCIPAL_POINT or CALIB_FIX_FOCAL_LENGTH are specified, some or all of fx, fy, cx, cy must be initialized before calling the function.
distCoeffs	Input/output vector of distortion coefficients \(\distcoeffs\).
rvecs	Output vector of rotation vectors (Rodrigues ) estimated for each pattern view (e.g. std::vector<cv::Mat>>). That is, each i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter description) brings the calibration pattern from the object coordinate space (in which object points are specified) to the camera coordinate space. In more technical terms, the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space to camera coordinate space. Due to its duality, this tuple is equivalent to the position of the calibration pattern with respect to the camera coordinate space.
tvecs	Output vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. Order of deviations values: \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. Order of deviations values: \((R_0, T_0, \dotsc , R_{M - 1}, T_{M - 1})\) where M is the number of pattern views. \(R_i, T_i\) are concatenated 1x3 vectors.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of the following values: CALIB_USE_INTRINSIC_GUESS cameraMatrix contains valid initial values of fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image center ( imageSize is used), and focal distances are computed in a least-squares fashion. Note, that if intrinsic parameters are known, there is no need to use this function just to estimate extrinsic parameters. Use solvePnP instead. CALIB_FIX_PRINCIPAL_POINT The principal point is not changed during the global optimization. It stays at the center or at a different location specified when CALIB_USE_INTRINSIC_GUESS is set too. CALIB_FIX_ASPECT_RATIO The functions consider only fy as a free parameter. The ratio fx/fy stays the same as in the input cameraMatrix . When CALIB_USE_INTRINSIC_GUESS is not set, the actual input values of fx and fy are ignored, only their ratio is computed and used further. CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients \((p_1, p_2)\) are set to zeros and stay zero. CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global optimization if CALIB_USE_INTRINSIC_GUESS is set. CALIB_FIX_K1,..., CALIB_FIX_K6 The corresponding radial distortion coefficient is not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_RATIONAL_MODEL Coefficients k4, k5, and k6 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the rational model and return 8 coefficients or more. CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the thin prism model and return 12 coefficients or more. CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the tilted sensor model and return 14 coefficients. CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000] and [BouguetMCT] . The coordinates of 3D object points and their corresponding 2D projections in each view must be specified. That may be achieved by using an object with known geometry and easily detectable feature points. Such an object is called a calibration rig or calibration pattern, and OpenCV has built-in support for a chessboard as a calibration rig (see findChessboardCorners). Currently, initialization of intrinsic parameters (when CALIB_USE_INTRINSIC_GUESS is not set) is only implemented for planar calibration patterns (where Z-coordinates of the object points must be all zeros). 3D calibration rigs can also be used as long as initial cameraMatrix is provided.

The algorithm performs the following steps:

Compute the initial intrinsic parameters (the option only available for planar calibration patterns) or read them from the input parameters. The distortion coefficients are all set to zeros initially unless some of CALIB_FIX_K? are specified.
Estimate the initial camera pose as if the intrinsic parameters have been already known. This is done using solvePnP .
Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error, that is, the total sum of squared distances between the observed feature points imagePoints and the projected (using the current estimates for camera parameters and the poses) object points objectPoints. See projectPoints for details.

Note: If you use a non-square (i.e. non-N-by-N) grid and findChessboardCorners for calibration, and calibrateCamera returns bad values (zero distortion coefficients, \(c_x\) and \(c_y\) very far from the image center, and/or large differences between \(f_x\) and \(f_y\) (ratios of 10:1 or more)), then you are probably using patternSize=cvSize(rows,cols) instead of using patternSize=cvSize(cols,rows) in findChessboardCorners.; The function may throw exceptions, if unsupported combination of parameters is provided or the system is underconstrained.

See also: calibrateCameraRO, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraExtended() [8/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	perViewErrors,
		int	flags )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

Parameters

objectPoints	In the new interface it is a vector of vectors of calibration pattern points in the calibration pattern coordinate space (e.g. std::vector<std::vector<cv::Vec3f>>). The outer vector contains as many elements as the number of pattern views. If the same calibration pattern is shown in each view and it is fully visible, all the vectors will be the same. Although, it is possible to use partially occluded patterns or even different patterns in different views. Then, the vectors will be different. Although the points are 3D, they all lie in the calibration pattern's XY coordinate plane (thus 0 in the Z-coordinate), if the used calibration pattern is a planar rig. In the old interface all the vectors of object points from different views are concatenated together.
imagePoints	In the new interface it is a vector of vectors of the projections of calibration pattern points (e.g. std::vector<std::vector<cv::Vec2f>>). imagePoints.size() and objectPoints.size(), and imagePoints[i].size() and objectPoints[i].size() for each i, must be equal, respectively. In the old interface all the vectors of object points from different views are concatenated together.
imageSize	Size of the image used only to initialize the camera intrinsic matrix.
cameraMatrix	Input/output 3x3 floating-point camera intrinsic matrix \(\cameramatrix{A}\) . If CALIB_USE_INTRINSIC_GUESS and/or CALIB_FIX_ASPECT_RATIO, CALIB_FIX_PRINCIPAL_POINT or CALIB_FIX_FOCAL_LENGTH are specified, some or all of fx, fy, cx, cy must be initialized before calling the function.
distCoeffs	Input/output vector of distortion coefficients \(\distcoeffs\).
rvecs	Output vector of rotation vectors (Rodrigues ) estimated for each pattern view (e.g. std::vector<cv::Mat>>). That is, each i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter description) brings the calibration pattern from the object coordinate space (in which object points are specified) to the camera coordinate space. In more technical terms, the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space to camera coordinate space. Due to its duality, this tuple is equivalent to the position of the calibration pattern with respect to the camera coordinate space.
tvecs	Output vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. Order of deviations values: \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. Order of deviations values: \((R_0, T_0, \dotsc , R_{M - 1}, T_{M - 1})\) where M is the number of pattern views. \(R_i, T_i\) are concatenated 1x3 vectors.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of the following values: CALIB_USE_INTRINSIC_GUESS cameraMatrix contains valid initial values of fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image center ( imageSize is used), and focal distances are computed in a least-squares fashion. Note, that if intrinsic parameters are known, there is no need to use this function just to estimate extrinsic parameters. Use solvePnP instead. CALIB_FIX_PRINCIPAL_POINT The principal point is not changed during the global optimization. It stays at the center or at a different location specified when CALIB_USE_INTRINSIC_GUESS is set too. CALIB_FIX_ASPECT_RATIO The functions consider only fy as a free parameter. The ratio fx/fy stays the same as in the input cameraMatrix . When CALIB_USE_INTRINSIC_GUESS is not set, the actual input values of fx and fy are ignored, only their ratio is computed and used further. CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients \((p_1, p_2)\) are set to zeros and stay zero. CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global optimization if CALIB_USE_INTRINSIC_GUESS is set. CALIB_FIX_K1,..., CALIB_FIX_K6 The corresponding radial distortion coefficient is not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_RATIONAL_MODEL Coefficients k4, k5, and k6 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the rational model and return 8 coefficients or more. CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the thin prism model and return 12 coefficients or more. CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the tilted sensor model and return 14 coefficients. CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000] and [BouguetMCT] . The coordinates of 3D object points and their corresponding 2D projections in each view must be specified. That may be achieved by using an object with known geometry and easily detectable feature points. Such an object is called a calibration rig or calibration pattern, and OpenCV has built-in support for a chessboard as a calibration rig (see findChessboardCorners). Currently, initialization of intrinsic parameters (when CALIB_USE_INTRINSIC_GUESS is not set) is only implemented for planar calibration patterns (where Z-coordinates of the object points must be all zeros). 3D calibration rigs can also be used as long as initial cameraMatrix is provided.

The algorithm performs the following steps:

Compute the initial intrinsic parameters (the option only available for planar calibration patterns) or read them from the input parameters. The distortion coefficients are all set to zeros initially unless some of CALIB_FIX_K? are specified.
Estimate the initial camera pose as if the intrinsic parameters have been already known. This is done using solvePnP .
Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error, that is, the total sum of squared distances between the observed feature points imagePoints and the projected (using the current estimates for camera parameters and the poses) object points objectPoints. See projectPoints for details.

Note: If you use a non-square (i.e. non-N-by-N) grid and findChessboardCorners for calibration, and calibrateCamera returns bad values (zero distortion coefficients, \(c_x\) and \(c_y\) very far from the image center, and/or large differences between \(f_x\) and \(f_y\) (ratios of 10:1 or more)), then you are probably using patternSize=cvSize(rows,cols) instead of using patternSize=cvSize(cols,rows) in findChessboardCorners.; The function may throw exceptions, if unsupported combination of parameters is provided or the system is underconstrained.

See also: calibrateCameraRO, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraExtended() [9/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	perViewErrors,
		int	flags,
		TermCriteria	criteria )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

Parameters

objectPoints	In the new interface it is a vector of vectors of calibration pattern points in the calibration pattern coordinate space (e.g. std::vector<std::vector<cv::Vec3f>>). The outer vector contains as many elements as the number of pattern views. If the same calibration pattern is shown in each view and it is fully visible, all the vectors will be the same. Although, it is possible to use partially occluded patterns or even different patterns in different views. Then, the vectors will be different. Although the points are 3D, they all lie in the calibration pattern's XY coordinate plane (thus 0 in the Z-coordinate), if the used calibration pattern is a planar rig. In the old interface all the vectors of object points from different views are concatenated together.
imagePoints	In the new interface it is a vector of vectors of the projections of calibration pattern points (e.g. std::vector<std::vector<cv::Vec2f>>). imagePoints.size() and objectPoints.size(), and imagePoints[i].size() and objectPoints[i].size() for each i, must be equal, respectively. In the old interface all the vectors of object points from different views are concatenated together.
imageSize	Size of the image used only to initialize the camera intrinsic matrix.
cameraMatrix	Input/output 3x3 floating-point camera intrinsic matrix \(\cameramatrix{A}\) . If CALIB_USE_INTRINSIC_GUESS and/or CALIB_FIX_ASPECT_RATIO, CALIB_FIX_PRINCIPAL_POINT or CALIB_FIX_FOCAL_LENGTH are specified, some or all of fx, fy, cx, cy must be initialized before calling the function.
distCoeffs	Input/output vector of distortion coefficients \(\distcoeffs\).
rvecs	Output vector of rotation vectors (Rodrigues ) estimated for each pattern view (e.g. std::vector<cv::Mat>>). That is, each i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter description) brings the calibration pattern from the object coordinate space (in which object points are specified) to the camera coordinate space. In more technical terms, the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space to camera coordinate space. Due to its duality, this tuple is equivalent to the position of the calibration pattern with respect to the camera coordinate space.
tvecs	Output vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. Order of deviations values: \((f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, s_4, \tau_x, \tau_y)\) If one of parameters is not estimated, it's deviation is equals to zero.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. Order of deviations values: \((R_0, T_0, \dotsc , R_{M - 1}, T_{M - 1})\) where M is the number of pattern views. \(R_i, T_i\) are concatenated 1x3 vectors.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of the following values: CALIB_USE_INTRINSIC_GUESS cameraMatrix contains valid initial values of fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image center ( imageSize is used), and focal distances are computed in a least-squares fashion. Note, that if intrinsic parameters are known, there is no need to use this function just to estimate extrinsic parameters. Use solvePnP instead. CALIB_FIX_PRINCIPAL_POINT The principal point is not changed during the global optimization. It stays at the center or at a different location specified when CALIB_USE_INTRINSIC_GUESS is set too. CALIB_FIX_ASPECT_RATIO The functions consider only fy as a free parameter. The ratio fx/fy stays the same as in the input cameraMatrix . When CALIB_USE_INTRINSIC_GUESS is not set, the actual input values of fx and fy are ignored, only their ratio is computed and used further. CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients \((p_1, p_2)\) are set to zeros and stay zero. CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global optimization if CALIB_USE_INTRINSIC_GUESS is set. CALIB_FIX_K1,..., CALIB_FIX_K6 The corresponding radial distortion coefficient is not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_RATIONAL_MODEL Coefficients k4, k5, and k6 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the rational model and return 8 coefficients or more. CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the thin prism model and return 12 coefficients or more. CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the tilted sensor model and return 14 coefficients. CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000] and [BouguetMCT] . The coordinates of 3D object points and their corresponding 2D projections in each view must be specified. That may be achieved by using an object with known geometry and easily detectable feature points. Such an object is called a calibration rig or calibration pattern, and OpenCV has built-in support for a chessboard as a calibration rig (see findChessboardCorners). Currently, initialization of intrinsic parameters (when CALIB_USE_INTRINSIC_GUESS is not set) is only implemented for planar calibration patterns (where Z-coordinates of the object points must be all zeros). 3D calibration rigs can also be used as long as initial cameraMatrix is provided.

The algorithm performs the following steps:

Compute the initial intrinsic parameters (the option only available for planar calibration patterns) or read them from the input parameters. The distortion coefficients are all set to zeros initially unless some of CALIB_FIX_K? are specified.
Estimate the initial camera pose as if the intrinsic parameters have been already known. This is done using solvePnP .
Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error, that is, the total sum of squared distances between the observed feature points imagePoints and the projected (using the current estimates for camera parameters and the poses) object points objectPoints. See projectPoints for details.

Note: If you use a non-square (i.e. non-N-by-N) grid and findChessboardCorners for calibration, and calibrateCamera returns bad values (zero distortion coefficients, \(c_x\) and \(c_y\) very far from the image center, and/or large differences between \(f_x\) and \(f_y\) (ratios of 10:1 or more)), then you are probably using patternSize=cvSize(rows,cols) instead of using patternSize=cvSize(cols,rows) in findChessboardCorners.; The function may throw exceptions, if unsupported combination of parameters is provided or the system is underconstrained.

See also: calibrateCameraRO, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraRO() [1/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraRO	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCameraRO() [2/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraRO	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		int	flags )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCameraRO() [3/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraRO	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		int	flags,
		in Vec3d	criteria )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCameraRO() [4/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraRO	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCameraRO() [5/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraRO	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		int	flags )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCameraRO() [6/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraRO	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		int	flags,
		in(double type, double maxCount, double epsilon)	criteria )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCameraRO() [7/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraRO	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCameraRO() [8/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraRO	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		int	flags )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCameraRO() [9/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraRO	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		int	flags,
		TermCriteria	criteria )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ calibrateCameraROExtended() [1/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraROExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	stdDeviationsObjPoints,
		Mat	perViewErrors )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

This function is an extension of calibrateCamera with the method of releasing object which was proposed in [strobl2011iccv]. In many common cases with inaccurate, unmeasured, roughly planar targets (calibration plates), this method can dramatically improve the precision of the estimated camera parameters. Both the object-releasing method and standard method are supported by this function. Use the parameter iFixedPoint for method selection. In the internal implementation, calibrateCamera is a wrapper for this function.

Parameters

objectPoints	Vector of vectors of calibration pattern points in the calibration pattern coordinate space. See calibrateCamera for details. If the method of releasing object to be used, the identical calibration board must be used in each view and it must be fully visible, and all objectPoints[i] must be the same and all points should be roughly close to a plane. The calibration target has to be rigid, or at least static if the camera (rather than the calibration target) is shifted for grabbing images.
imagePoints	Vector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSize	Size of the image used only to initialize the intrinsic camera matrix.
iFixedPoint	The index of the 3D object point in objectPoints[0] to be fixed. It also acts as a switch for calibration method selection. If object-releasing method to be used, pass in the parameter in the range of [1, objectPoints[0].size()-2], otherwise a value out of this range will make standard calibration method selected. Usually the top-right corner point of the calibration board grid is recommended to be fixed when object-releasing method being utilized. According to [strobl2011iccv], two other points are also fixed. In this implementation, objectPoints[0].front and objectPoints[0].back.z are used. With object-releasing method, accurate rvecs, tvecs and newObjPoints are only possible if coordinates of these three fixed points are accurate enough.
cameraMatrix	Output 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffs	Output vector of distortion coefficients. See calibrateCamera for details.
rvecs	Output vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecs	Output vector of translation vectors estimated for each pattern view.
newObjPoints	The updated output vector of calibration pattern points. The coordinates might be scaled based on three fixed points. The returned coordinates are accurate only if the above mentioned three fixed points are accurate. If not needed, noArray() can be passed in. This parameter is ignored with standard calibration method.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPoints	Output vector of standard deviations estimated for refined coordinates of calibration pattern points. It has the same size and order as objectPoints[0] vector. This parameter is ignored with standard calibration method.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of some predefined values. See calibrateCamera for details. If the method of releasing object is used, the calibration time may be much longer. CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with potentially less precise and less stable in some rare cases.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000], [BouguetMCT] and [strobl2011iccv]. See calibrateCamera for other detailed explanations.

See also: calibrateCamera, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraROExtended() [2/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraROExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	stdDeviationsObjPoints,
		Mat	perViewErrors,
		int	flags )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

This function is an extension of calibrateCamera with the method of releasing object which was proposed in [strobl2011iccv]. In many common cases with inaccurate, unmeasured, roughly planar targets (calibration plates), this method can dramatically improve the precision of the estimated camera parameters. Both the object-releasing method and standard method are supported by this function. Use the parameter iFixedPoint for method selection. In the internal implementation, calibrateCamera is a wrapper for this function.

Parameters

objectPoints	Vector of vectors of calibration pattern points in the calibration pattern coordinate space. See calibrateCamera for details. If the method of releasing object to be used, the identical calibration board must be used in each view and it must be fully visible, and all objectPoints[i] must be the same and all points should be roughly close to a plane. The calibration target has to be rigid, or at least static if the camera (rather than the calibration target) is shifted for grabbing images.
imagePoints	Vector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSize	Size of the image used only to initialize the intrinsic camera matrix.
iFixedPoint	The index of the 3D object point in objectPoints[0] to be fixed. It also acts as a switch for calibration method selection. If object-releasing method to be used, pass in the parameter in the range of [1, objectPoints[0].size()-2], otherwise a value out of this range will make standard calibration method selected. Usually the top-right corner point of the calibration board grid is recommended to be fixed when object-releasing method being utilized. According to [strobl2011iccv], two other points are also fixed. In this implementation, objectPoints[0].front and objectPoints[0].back.z are used. With object-releasing method, accurate rvecs, tvecs and newObjPoints are only possible if coordinates of these three fixed points are accurate enough.
cameraMatrix	Output 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffs	Output vector of distortion coefficients. See calibrateCamera for details.
rvecs	Output vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecs	Output vector of translation vectors estimated for each pattern view.
newObjPoints	The updated output vector of calibration pattern points. The coordinates might be scaled based on three fixed points. The returned coordinates are accurate only if the above mentioned three fixed points are accurate. If not needed, noArray() can be passed in. This parameter is ignored with standard calibration method.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPoints	Output vector of standard deviations estimated for refined coordinates of calibration pattern points. It has the same size and order as objectPoints[0] vector. This parameter is ignored with standard calibration method.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of some predefined values. See calibrateCamera for details. If the method of releasing object is used, the calibration time may be much longer. CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with potentially less precise and less stable in some rare cases.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000], [BouguetMCT] and [strobl2011iccv]. See calibrateCamera for other detailed explanations.

See also: calibrateCamera, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraROExtended() [3/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraROExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in Vec2d	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	stdDeviationsObjPoints,
		Mat	perViewErrors,
		int	flags,
		in Vec3d	criteria )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

This function is an extension of calibrateCamera with the method of releasing object which was proposed in [strobl2011iccv]. In many common cases with inaccurate, unmeasured, roughly planar targets (calibration plates), this method can dramatically improve the precision of the estimated camera parameters. Both the object-releasing method and standard method are supported by this function. Use the parameter iFixedPoint for method selection. In the internal implementation, calibrateCamera is a wrapper for this function.

Parameters

objectPoints	Vector of vectors of calibration pattern points in the calibration pattern coordinate space. See calibrateCamera for details. If the method of releasing object to be used, the identical calibration board must be used in each view and it must be fully visible, and all objectPoints[i] must be the same and all points should be roughly close to a plane. The calibration target has to be rigid, or at least static if the camera (rather than the calibration target) is shifted for grabbing images.
imagePoints	Vector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSize	Size of the image used only to initialize the intrinsic camera matrix.
iFixedPoint	The index of the 3D object point in objectPoints[0] to be fixed. It also acts as a switch for calibration method selection. If object-releasing method to be used, pass in the parameter in the range of [1, objectPoints[0].size()-2], otherwise a value out of this range will make standard calibration method selected. Usually the top-right corner point of the calibration board grid is recommended to be fixed when object-releasing method being utilized. According to [strobl2011iccv], two other points are also fixed. In this implementation, objectPoints[0].front and objectPoints[0].back.z are used. With object-releasing method, accurate rvecs, tvecs and newObjPoints are only possible if coordinates of these three fixed points are accurate enough.
cameraMatrix	Output 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffs	Output vector of distortion coefficients. See calibrateCamera for details.
rvecs	Output vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecs	Output vector of translation vectors estimated for each pattern view.
newObjPoints	The updated output vector of calibration pattern points. The coordinates might be scaled based on three fixed points. The returned coordinates are accurate only if the above mentioned three fixed points are accurate. If not needed, noArray() can be passed in. This parameter is ignored with standard calibration method.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPoints	Output vector of standard deviations estimated for refined coordinates of calibration pattern points. It has the same size and order as objectPoints[0] vector. This parameter is ignored with standard calibration method.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of some predefined values. See calibrateCamera for details. If the method of releasing object is used, the calibration time may be much longer. CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with potentially less precise and less stable in some rare cases.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000], [BouguetMCT] and [strobl2011iccv]. See calibrateCamera for other detailed explanations.

See also: calibrateCamera, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraROExtended() [4/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraROExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	stdDeviationsObjPoints,
		Mat	perViewErrors )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

This function is an extension of calibrateCamera with the method of releasing object which was proposed in [strobl2011iccv]. In many common cases with inaccurate, unmeasured, roughly planar targets (calibration plates), this method can dramatically improve the precision of the estimated camera parameters. Both the object-releasing method and standard method are supported by this function. Use the parameter iFixedPoint for method selection. In the internal implementation, calibrateCamera is a wrapper for this function.

Parameters

objectPoints	Vector of vectors of calibration pattern points in the calibration pattern coordinate space. See calibrateCamera for details. If the method of releasing object to be used, the identical calibration board must be used in each view and it must be fully visible, and all objectPoints[i] must be the same and all points should be roughly close to a plane. The calibration target has to be rigid, or at least static if the camera (rather than the calibration target) is shifted for grabbing images.
imagePoints	Vector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSize	Size of the image used only to initialize the intrinsic camera matrix.
iFixedPoint	The index of the 3D object point in objectPoints[0] to be fixed. It also acts as a switch for calibration method selection. If object-releasing method to be used, pass in the parameter in the range of [1, objectPoints[0].size()-2], otherwise a value out of this range will make standard calibration method selected. Usually the top-right corner point of the calibration board grid is recommended to be fixed when object-releasing method being utilized. According to [strobl2011iccv], two other points are also fixed. In this implementation, objectPoints[0].front and objectPoints[0].back.z are used. With object-releasing method, accurate rvecs, tvecs and newObjPoints are only possible if coordinates of these three fixed points are accurate enough.
cameraMatrix	Output 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffs	Output vector of distortion coefficients. See calibrateCamera for details.
rvecs	Output vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecs	Output vector of translation vectors estimated for each pattern view.
newObjPoints	The updated output vector of calibration pattern points. The coordinates might be scaled based on three fixed points. The returned coordinates are accurate only if the above mentioned three fixed points are accurate. If not needed, noArray() can be passed in. This parameter is ignored with standard calibration method.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPoints	Output vector of standard deviations estimated for refined coordinates of calibration pattern points. It has the same size and order as objectPoints[0] vector. This parameter is ignored with standard calibration method.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of some predefined values. See calibrateCamera for details. If the method of releasing object is used, the calibration time may be much longer. CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with potentially less precise and less stable in some rare cases.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000], [BouguetMCT] and [strobl2011iccv]. See calibrateCamera for other detailed explanations.

See also: calibrateCamera, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraROExtended() [5/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraROExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	stdDeviationsObjPoints,
		Mat	perViewErrors,
		int	flags )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

This function is an extension of calibrateCamera with the method of releasing object which was proposed in [strobl2011iccv]. In many common cases with inaccurate, unmeasured, roughly planar targets (calibration plates), this method can dramatically improve the precision of the estimated camera parameters. Both the object-releasing method and standard method are supported by this function. Use the parameter iFixedPoint for method selection. In the internal implementation, calibrateCamera is a wrapper for this function.

Parameters

objectPoints	Vector of vectors of calibration pattern points in the calibration pattern coordinate space. See calibrateCamera for details. If the method of releasing object to be used, the identical calibration board must be used in each view and it must be fully visible, and all objectPoints[i] must be the same and all points should be roughly close to a plane. The calibration target has to be rigid, or at least static if the camera (rather than the calibration target) is shifted for grabbing images.
imagePoints	Vector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSize	Size of the image used only to initialize the intrinsic camera matrix.
iFixedPoint	The index of the 3D object point in objectPoints[0] to be fixed. It also acts as a switch for calibration method selection. If object-releasing method to be used, pass in the parameter in the range of [1, objectPoints[0].size()-2], otherwise a value out of this range will make standard calibration method selected. Usually the top-right corner point of the calibration board grid is recommended to be fixed when object-releasing method being utilized. According to [strobl2011iccv], two other points are also fixed. In this implementation, objectPoints[0].front and objectPoints[0].back.z are used. With object-releasing method, accurate rvecs, tvecs and newObjPoints are only possible if coordinates of these three fixed points are accurate enough.
cameraMatrix	Output 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffs	Output vector of distortion coefficients. See calibrateCamera for details.
rvecs	Output vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecs	Output vector of translation vectors estimated for each pattern view.
newObjPoints	The updated output vector of calibration pattern points. The coordinates might be scaled based on three fixed points. The returned coordinates are accurate only if the above mentioned three fixed points are accurate. If not needed, noArray() can be passed in. This parameter is ignored with standard calibration method.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPoints	Output vector of standard deviations estimated for refined coordinates of calibration pattern points. It has the same size and order as objectPoints[0] vector. This parameter is ignored with standard calibration method.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of some predefined values. See calibrateCamera for details. If the method of releasing object is used, the calibration time may be much longer. CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with potentially less precise and less stable in some rare cases.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000], [BouguetMCT] and [strobl2011iccv]. See calibrateCamera for other detailed explanations.

See also: calibrateCamera, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraROExtended() [6/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraROExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		in(double width, double height)	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	stdDeviationsObjPoints,
		Mat	perViewErrors,
		int	flags,
		in(double type, double maxCount, double epsilon)	criteria )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

This function is an extension of calibrateCamera with the method of releasing object which was proposed in [strobl2011iccv]. In many common cases with inaccurate, unmeasured, roughly planar targets (calibration plates), this method can dramatically improve the precision of the estimated camera parameters. Both the object-releasing method and standard method are supported by this function. Use the parameter iFixedPoint for method selection. In the internal implementation, calibrateCamera is a wrapper for this function.

Parameters

objectPoints	Vector of vectors of calibration pattern points in the calibration pattern coordinate space. See calibrateCamera for details. If the method of releasing object to be used, the identical calibration board must be used in each view and it must be fully visible, and all objectPoints[i] must be the same and all points should be roughly close to a plane. The calibration target has to be rigid, or at least static if the camera (rather than the calibration target) is shifted for grabbing images.
imagePoints	Vector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSize	Size of the image used only to initialize the intrinsic camera matrix.
iFixedPoint	The index of the 3D object point in objectPoints[0] to be fixed. It also acts as a switch for calibration method selection. If object-releasing method to be used, pass in the parameter in the range of [1, objectPoints[0].size()-2], otherwise a value out of this range will make standard calibration method selected. Usually the top-right corner point of the calibration board grid is recommended to be fixed when object-releasing method being utilized. According to [strobl2011iccv], two other points are also fixed. In this implementation, objectPoints[0].front and objectPoints[0].back.z are used. With object-releasing method, accurate rvecs, tvecs and newObjPoints are only possible if coordinates of these three fixed points are accurate enough.
cameraMatrix	Output 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffs	Output vector of distortion coefficients. See calibrateCamera for details.
rvecs	Output vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecs	Output vector of translation vectors estimated for each pattern view.
newObjPoints	The updated output vector of calibration pattern points. The coordinates might be scaled based on three fixed points. The returned coordinates are accurate only if the above mentioned three fixed points are accurate. If not needed, noArray() can be passed in. This parameter is ignored with standard calibration method.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPoints	Output vector of standard deviations estimated for refined coordinates of calibration pattern points. It has the same size and order as objectPoints[0] vector. This parameter is ignored with standard calibration method.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of some predefined values. See calibrateCamera for details. If the method of releasing object is used, the calibration time may be much longer. CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with potentially less precise and less stable in some rare cases.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000], [BouguetMCT] and [strobl2011iccv]. See calibrateCamera for other detailed explanations.

See also: calibrateCamera, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraROExtended() [7/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraROExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	stdDeviationsObjPoints,
		Mat	perViewErrors )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

This function is an extension of calibrateCamera with the method of releasing object which was proposed in [strobl2011iccv]. In many common cases with inaccurate, unmeasured, roughly planar targets (calibration plates), this method can dramatically improve the precision of the estimated camera parameters. Both the object-releasing method and standard method are supported by this function. Use the parameter iFixedPoint for method selection. In the internal implementation, calibrateCamera is a wrapper for this function.

Parameters

objectPoints	Vector of vectors of calibration pattern points in the calibration pattern coordinate space. See calibrateCamera for details. If the method of releasing object to be used, the identical calibration board must be used in each view and it must be fully visible, and all objectPoints[i] must be the same and all points should be roughly close to a plane. The calibration target has to be rigid, or at least static if the camera (rather than the calibration target) is shifted for grabbing images.
imagePoints	Vector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSize	Size of the image used only to initialize the intrinsic camera matrix.
iFixedPoint	The index of the 3D object point in objectPoints[0] to be fixed. It also acts as a switch for calibration method selection. If object-releasing method to be used, pass in the parameter in the range of [1, objectPoints[0].size()-2], otherwise a value out of this range will make standard calibration method selected. Usually the top-right corner point of the calibration board grid is recommended to be fixed when object-releasing method being utilized. According to [strobl2011iccv], two other points are also fixed. In this implementation, objectPoints[0].front and objectPoints[0].back.z are used. With object-releasing method, accurate rvecs, tvecs and newObjPoints are only possible if coordinates of these three fixed points are accurate enough.
cameraMatrix	Output 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffs	Output vector of distortion coefficients. See calibrateCamera for details.
rvecs	Output vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecs	Output vector of translation vectors estimated for each pattern view.
newObjPoints	The updated output vector of calibration pattern points. The coordinates might be scaled based on three fixed points. The returned coordinates are accurate only if the above mentioned three fixed points are accurate. If not needed, noArray() can be passed in. This parameter is ignored with standard calibration method.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPoints	Output vector of standard deviations estimated for refined coordinates of calibration pattern points. It has the same size and order as objectPoints[0] vector. This parameter is ignored with standard calibration method.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of some predefined values. See calibrateCamera for details. If the method of releasing object is used, the calibration time may be much longer. CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with potentially less precise and less stable in some rare cases.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000], [BouguetMCT] and [strobl2011iccv]. See calibrateCamera for other detailed explanations.

See also: calibrateCamera, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraROExtended() [8/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraROExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	stdDeviationsObjPoints,
		Mat	perViewErrors,
		int	flags )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

This function is an extension of calibrateCamera with the method of releasing object which was proposed in [strobl2011iccv]. In many common cases with inaccurate, unmeasured, roughly planar targets (calibration plates), this method can dramatically improve the precision of the estimated camera parameters. Both the object-releasing method and standard method are supported by this function. Use the parameter iFixedPoint for method selection. In the internal implementation, calibrateCamera is a wrapper for this function.

Parameters

objectPoints	Vector of vectors of calibration pattern points in the calibration pattern coordinate space. See calibrateCamera for details. If the method of releasing object to be used, the identical calibration board must be used in each view and it must be fully visible, and all objectPoints[i] must be the same and all points should be roughly close to a plane. The calibration target has to be rigid, or at least static if the camera (rather than the calibration target) is shifted for grabbing images.
imagePoints	Vector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSize	Size of the image used only to initialize the intrinsic camera matrix.
iFixedPoint	The index of the 3D object point in objectPoints[0] to be fixed. It also acts as a switch for calibration method selection. If object-releasing method to be used, pass in the parameter in the range of [1, objectPoints[0].size()-2], otherwise a value out of this range will make standard calibration method selected. Usually the top-right corner point of the calibration board grid is recommended to be fixed when object-releasing method being utilized. According to [strobl2011iccv], two other points are also fixed. In this implementation, objectPoints[0].front and objectPoints[0].back.z are used. With object-releasing method, accurate rvecs, tvecs and newObjPoints are only possible if coordinates of these three fixed points are accurate enough.
cameraMatrix	Output 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffs	Output vector of distortion coefficients. See calibrateCamera for details.
rvecs	Output vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecs	Output vector of translation vectors estimated for each pattern view.
newObjPoints	The updated output vector of calibration pattern points. The coordinates might be scaled based on three fixed points. The returned coordinates are accurate only if the above mentioned three fixed points are accurate. If not needed, noArray() can be passed in. This parameter is ignored with standard calibration method.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPoints	Output vector of standard deviations estimated for refined coordinates of calibration pattern points. It has the same size and order as objectPoints[0] vector. This parameter is ignored with standard calibration method.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of some predefined values. See calibrateCamera for details. If the method of releasing object is used, the calibration time may be much longer. CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with potentially less precise and less stable in some rare cases.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000], [BouguetMCT] and [strobl2011iccv]. See calibrateCamera for other detailed explanations.

See also: calibrateCamera, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateCameraROExtended() [9/9]

static double OpenCVForUnity.Calib3dModule.Calib3d.calibrateCameraROExtended	(	List< Mat >	objectPoints,
		List< Mat >	imagePoints,
		Size	imageSize,
		int	iFixedPoint,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		List< Mat >	rvecs,
		List< Mat >	tvecs,
		Mat	newObjPoints,
		Mat	stdDeviationsIntrinsics,
		Mat	stdDeviationsExtrinsics,
		Mat	stdDeviationsObjPoints,
		Mat	perViewErrors,
		int	flags,
		TermCriteria	criteria )

static

Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.

This function is an extension of calibrateCamera with the method of releasing object which was proposed in [strobl2011iccv]. In many common cases with inaccurate, unmeasured, roughly planar targets (calibration plates), this method can dramatically improve the precision of the estimated camera parameters. Both the object-releasing method and standard method are supported by this function. Use the parameter iFixedPoint for method selection. In the internal implementation, calibrateCamera is a wrapper for this function.

Parameters

objectPoints	Vector of vectors of calibration pattern points in the calibration pattern coordinate space. See calibrateCamera for details. If the method of releasing object to be used, the identical calibration board must be used in each view and it must be fully visible, and all objectPoints[i] must be the same and all points should be roughly close to a plane. The calibration target has to be rigid, or at least static if the camera (rather than the calibration target) is shifted for grabbing images.
imagePoints	Vector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSize	Size of the image used only to initialize the intrinsic camera matrix.
iFixedPoint	The index of the 3D object point in objectPoints[0] to be fixed. It also acts as a switch for calibration method selection. If object-releasing method to be used, pass in the parameter in the range of [1, objectPoints[0].size()-2], otherwise a value out of this range will make standard calibration method selected. Usually the top-right corner point of the calibration board grid is recommended to be fixed when object-releasing method being utilized. According to [strobl2011iccv], two other points are also fixed. In this implementation, objectPoints[0].front and objectPoints[0].back.z are used. With object-releasing method, accurate rvecs, tvecs and newObjPoints are only possible if coordinates of these three fixed points are accurate enough.
cameraMatrix	Output 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffs	Output vector of distortion coefficients. See calibrateCamera for details.
rvecs	Output vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecs	Output vector of translation vectors estimated for each pattern view.
newObjPoints	The updated output vector of calibration pattern points. The coordinates might be scaled based on three fixed points. The returned coordinates are accurate only if the above mentioned three fixed points are accurate. If not needed, noArray() can be passed in. This parameter is ignored with standard calibration method.
stdDeviationsIntrinsics	Output vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsics	Output vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPoints	Output vector of standard deviations estimated for refined coordinates of calibration pattern points. It has the same size and order as objectPoints[0] vector. This parameter is ignored with standard calibration method.
perViewErrors	Output vector of the RMS re-projection error estimated for each pattern view.
flags	Different flags that may be zero or a combination of some predefined values. See calibrateCamera for details. If the method of releasing object is used, the calibration time may be much longer. CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with potentially less precise and less stable in some rare cases.
criteria	Termination criteria for the iterative optimization algorithm.

Returns: the overall RMS re-projection error.

The function estimates the intrinsic camera parameters and extrinsic parameters for each of the views. The algorithm is based on [Zhang2000], [BouguetMCT] and [strobl2011iccv]. See calibrateCamera for other detailed explanations.

See also: calibrateCamera, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort

◆ calibrateHandEye() [1/2]

static void OpenCVForUnity.Calib3dModule.Calib3d.calibrateHandEye	(	List< Mat >	R_gripper2base,
		List< Mat >	t_gripper2base,
		List< Mat >	R_target2cam,
		List< Mat >	t_target2cam,
		Mat	R_cam2gripper,
		Mat	t_cam2gripper )

static

Computes Hand-Eye calibration: \(_{}^{g}\textrm{T}_c\).

The function performs the Hand-Eye calibration using various methods. One approach consists in estimating the rotation then the translation (separable solutions) and the following methods are implemented:

R. Tsai, R. Lenz A New Technique for Fully Autonomous and Efficient 3D Robotics Hand/EyeCalibration [Tsai89]
F. Park, B. Martin Robot Sensor Calibration: Solving AX = XB on the Euclidean Group [Park94]
R. Horaud, F. Dornaika Hand-Eye Calibration [Horaud95]

Another approach consists in estimating simultaneously the rotation and the translation (simultaneous solutions), with the following implemented methods:

N. Andreff, R. Horaud, B. Espiau On-line Hand-Eye Calibration [Andreff99]
K. Daniilidis Hand-Eye Calibration Using Dual Quaternions [Daniilidis98]

The following picture describes the Hand-Eye calibration problem where the transformation between a camera ("eye") mounted on a robot gripper ("hand") has to be estimated. This configuration is called eye-in-hand.

The eye-to-hand configuration consists in a static camera observing a calibration pattern mounted on the robot end-effector. The transformation from the camera to the robot base frame can then be estimated by inputting the suitable transformations to the function, see below.

The calibration procedure is the following:

a static calibration pattern is used to estimate the transformation between the target frame and the camera frame
the robot gripper is moved in order to acquire several poses
for each pose, the homogeneous transformation between the gripper frame and the robot base frame is recorded using for instance the robot kinematics
\[ \begin{bmatrix} X_b\\ Y_b\\ Z_b\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{b}\textrm{R}_g & _{}^{b}\textrm{t}_g \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_g\\ Y_g\\ Z_g\\ 1 \end{bmatrix} \]
for each pose, the homogeneous transformation between the calibration target frame and the camera frame is recorded using for instance a pose estimation method (PnP) from 2D-3D point correspondences
\[ \begin{bmatrix} X_c\\ Y_c\\ Z_c\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{c}\textrm{R}_t & _{}^{c}\textrm{t}_t \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_t\\ Y_t\\ Z_t\\ 1 \end{bmatrix} \]

The Hand-Eye calibration procedure returns the following homogeneous transformation

\[ \begin{bmatrix} X_g\\ Y_g\\ Z_g\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{g}\textrm{R}_c & _{}^{g}\textrm{t}_c \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_c\\ Y_c\\ Z_c\\ 1 \end{bmatrix} \]

This problem is also known as solving the \(\mathbf{A}\mathbf{X}=\mathbf{X}\mathbf{B}\) equation:

for an eye-in-hand configuration
\[ \begin{align*} ^{b}{\textrm{T}_g}^{(1)} \hspace{0.2em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(1)} &= \hspace{0.1em} ^{b}{\textrm{T}_g}^{(2)} \hspace{0.2em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} \\ (^{b}{\textrm{T}_g}^{(2)})^{-1} \hspace{0.2em} ^{b}{\textrm{T}_g}^{(1)} \hspace{0.2em} ^{g}\textrm{T}_c &= \hspace{0.1em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} (^{c}{\textrm{T}_t}^{(1)})^{-1} \\ \textrm{A}_i \textrm{X} &= \textrm{X} \textrm{B}_i \\ \end{align*} \]
for an eye-to-hand configuration
\[ \begin{align*} ^{g}{\textrm{T}_b}^{(1)} \hspace{0.2em} ^{b}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(1)} &= \hspace{0.1em} ^{g}{\textrm{T}_b}^{(2)} \hspace{0.2em} ^{b}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} \\ (^{g}{\textrm{T}_b}^{(2)})^{-1} \hspace{0.2em} ^{g}{\textrm{T}_b}^{(1)} \hspace{0.2em} ^{b}\textrm{T}_c &= \hspace{0.1em} ^{b}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} (^{c}{\textrm{T}_t}^{(1)})^{-1} \\ \textrm{A}_i \textrm{X} &= \textrm{X} \textrm{B}_i \\ \end{align*} \]

Note: Additional information can be found on this website.; A minimum of 2 motions with non parallel rotation axes are necessary to determine the hand-eye transformation. So at least 3 different poses are required, but it is strongly recommended to use many more poses.

◆ calibrateHandEye() [2/2]

static void OpenCVForUnity.Calib3dModule.Calib3d.calibrateHandEye	(	List< Mat >	R_gripper2base,
		List< Mat >	t_gripper2base,
		List< Mat >	R_target2cam,
		List< Mat >	t_target2cam,
		Mat	R_cam2gripper,
		Mat	t_cam2gripper,
		int	method )

static

Computes Hand-Eye calibration: \(_{}^{g}\textrm{T}_c\).

The function performs the Hand-Eye calibration using various methods. One approach consists in estimating the rotation then the translation (separable solutions) and the following methods are implemented:

R. Tsai, R. Lenz A New Technique for Fully Autonomous and Efficient 3D Robotics Hand/EyeCalibration [Tsai89]
F. Park, B. Martin Robot Sensor Calibration: Solving AX = XB on the Euclidean Group [Park94]
R. Horaud, F. Dornaika Hand-Eye Calibration [Horaud95]

Another approach consists in estimating simultaneously the rotation and the translation (simultaneous solutions), with the following implemented methods:

N. Andreff, R. Horaud, B. Espiau On-line Hand-Eye Calibration [Andreff99]
K. Daniilidis Hand-Eye Calibration Using Dual Quaternions [Daniilidis98]

The following picture describes the Hand-Eye calibration problem where the transformation between a camera ("eye") mounted on a robot gripper ("hand") has to be estimated. This configuration is called eye-in-hand.

The eye-to-hand configuration consists in a static camera observing a calibration pattern mounted on the robot end-effector. The transformation from the camera to the robot base frame can then be estimated by inputting the suitable transformations to the function, see below.

The calibration procedure is the following:

a static calibration pattern is used to estimate the transformation between the target frame and the camera frame
the robot gripper is moved in order to acquire several poses
for each pose, the homogeneous transformation between the gripper frame and the robot base frame is recorded using for instance the robot kinematics
\[ \begin{bmatrix} X_b\\ Y_b\\ Z_b\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{b}\textrm{R}_g & _{}^{b}\textrm{t}_g \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_g\\ Y_g\\ Z_g\\ 1 \end{bmatrix} \]
for each pose, the homogeneous transformation between the calibration target frame and the camera frame is recorded using for instance a pose estimation method (PnP) from 2D-3D point correspondences
\[ \begin{bmatrix} X_c\\ Y_c\\ Z_c\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{c}\textrm{R}_t & _{}^{c}\textrm{t}_t \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_t\\ Y_t\\ Z_t\\ 1 \end{bmatrix} \]

The Hand-Eye calibration procedure returns the following homogeneous transformation

\[ \begin{bmatrix} X_g\\ Y_g\\ Z_g\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{g}\textrm{R}_c & _{}^{g}\textrm{t}_c \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_c\\ Y_c\\ Z_c\\ 1 \end{bmatrix} \]

This problem is also known as solving the \(\mathbf{A}\mathbf{X}=\mathbf{X}\mathbf{B}\) equation:

for an eye-in-hand configuration
\[ \begin{align*} ^{b}{\textrm{T}_g}^{(1)} \hspace{0.2em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(1)} &= \hspace{0.1em} ^{b}{\textrm{T}_g}^{(2)} \hspace{0.2em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} \\ (^{b}{\textrm{T}_g}^{(2)})^{-1} \hspace{0.2em} ^{b}{\textrm{T}_g}^{(1)} \hspace{0.2em} ^{g}\textrm{T}_c &= \hspace{0.1em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} (^{c}{\textrm{T}_t}^{(1)})^{-1} \\ \textrm{A}_i \textrm{X} &= \textrm{X} \textrm{B}_i \\ \end{align*} \]
for an eye-to-hand configuration
\[ \begin{align*} ^{g}{\textrm{T}_b}^{(1)} \hspace{0.2em} ^{b}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(1)} &= \hspace{0.1em} ^{g}{\textrm{T}_b}^{(2)} \hspace{0.2em} ^{b}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} \\ (^{g}{\textrm{T}_b}^{(2)})^{-1} \hspace{0.2em} ^{g}{\textrm{T}_b}^{(1)} \hspace{0.2em} ^{b}\textrm{T}_c &= \hspace{0.1em} ^{b}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} (^{c}{\textrm{T}_t}^{(1)})^{-1} \\ \textrm{A}_i \textrm{X} &= \textrm{X} \textrm{B}_i \\ \end{align*} \]

Note: Additional information can be found on this website.; A minimum of 2 motions with non parallel rotation axes are necessary to determine the hand-eye transformation. So at least 3 different poses are required, but it is strongly recommended to use many more poses.

◆ calibrateRobotWorldHandEye() [1/2]

static void OpenCVForUnity.Calib3dModule.Calib3d.calibrateRobotWorldHandEye	(	List< Mat >	R_world2cam,
		List< Mat >	t_world2cam,
		List< Mat >	R_base2gripper,
		List< Mat >	t_base2gripper,
		Mat	R_base2world,
		Mat	t_base2world,
		Mat	R_gripper2cam,
		Mat	t_gripper2cam )

static

Computes Robot-World/Hand-Eye calibration: \(_{}^{w}\textrm{T}_b\) and \(_{}^{c}\textrm{T}_g\).

The function performs the Robot-World/Hand-Eye calibration using various methods. One approach consists in estimating the rotation then the translation (separable solutions):

M. Shah, Solving the robot-world/hand-eye calibration problem using the kronecker product [Shah2013SolvingTR]

Another approach consists in estimating simultaneously the rotation and the translation (simultaneous solutions), with the following implemented method:

A. Li, L. Wang, and D. Wu, Simultaneous robot-world and hand-eye calibration using dual-quaternions and kronecker product [Li2010SimultaneousRA]

The following picture describes the Robot-World/Hand-Eye calibration problem where the transformations between a robot and a world frame and between a robot gripper ("hand") and a camera ("eye") mounted at the robot end-effector have to be estimated.

The calibration procedure is the following:

a static calibration pattern is used to estimate the transformation between the target frame and the camera frame
the robot gripper is moved in order to acquire several poses
for each pose, the homogeneous transformation between the gripper frame and the robot base frame is recorded using for instance the robot kinematics
\[ \begin{bmatrix} X_g\\ Y_g\\ Z_g\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{g}\textrm{R}_b & _{}^{g}\textrm{t}_b \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_b\\ Y_b\\ Z_b\\ 1 \end{bmatrix} \]
for each pose, the homogeneous transformation between the calibration target frame (the world frame) and the camera frame is recorded using for instance a pose estimation method (PnP) from 2D-3D point correspondences
\[ \begin{bmatrix} X_c\\ Y_c\\ Z_c\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{c}\textrm{R}_w & _{}^{c}\textrm{t}_w \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_w\\ Y_w\\ Z_w\\ 1 \end{bmatrix} \]

The Robot-World/Hand-Eye calibration procedure returns the following homogeneous transformations

\[ \begin{bmatrix} X_w\\ Y_w\\ Z_w\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{w}\textrm{R}_b & _{}^{w}\textrm{t}_b \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_b\\ Y_b\\ Z_b\\ 1 \end{bmatrix} \]

\[ \begin{bmatrix} X_c\\ Y_c\\ Z_c\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{c}\textrm{R}_g & _{}^{c}\textrm{t}_g \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_g\\ Y_g\\ Z_g\\ 1 \end{bmatrix} \]

This problem is also known as solving the \(\mathbf{A}\mathbf{X}=\mathbf{Z}\mathbf{B}\) equation, with:

\(\mathbf{A} \Leftrightarrow \hspace{0.1em} _{}^{c}\textrm{T}_w\)
\(\mathbf{X} \Leftrightarrow \hspace{0.1em} _{}^{w}\textrm{T}_b\)
\(\mathbf{Z} \Leftrightarrow \hspace{0.1em} _{}^{c}\textrm{T}_g\)
\(\mathbf{B} \Leftrightarrow \hspace{0.1em} _{}^{g}\textrm{T}_b\)

Note: At least 3 measurements are required (input vectors size must be greater or equal to 3).

◆ calibrateRobotWorldHandEye() [2/2]

static void OpenCVForUnity.Calib3dModule.Calib3d.calibrateRobotWorldHandEye	(	List< Mat >	R_world2cam,
		List< Mat >	t_world2cam,
		List< Mat >	R_base2gripper,
		List< Mat >	t_base2gripper,
		Mat	R_base2world,
		Mat	t_base2world,
		Mat	R_gripper2cam,
		Mat	t_gripper2cam,
		int	method )

static

Computes Robot-World/Hand-Eye calibration: \(_{}^{w}\textrm{T}_b\) and \(_{}^{c}\textrm{T}_g\).

The function performs the Robot-World/Hand-Eye calibration using various methods. One approach consists in estimating the rotation then the translation (separable solutions):

M. Shah, Solving the robot-world/hand-eye calibration problem using the kronecker product [Shah2013SolvingTR]

Another approach consists in estimating simultaneously the rotation and the translation (simultaneous solutions), with the following implemented method:

A. Li, L. Wang, and D. Wu, Simultaneous robot-world and hand-eye calibration using dual-quaternions and kronecker product [Li2010SimultaneousRA]

The following picture describes the Robot-World/Hand-Eye calibration problem where the transformations between a robot and a world frame and between a robot gripper ("hand") and a camera ("eye") mounted at the robot end-effector have to be estimated.

The calibration procedure is the following:

a static calibration pattern is used to estimate the transformation between the target frame and the camera frame
the robot gripper is moved in order to acquire several poses
for each pose, the homogeneous transformation between the gripper frame and the robot base frame is recorded using for instance the robot kinematics
\[ \begin{bmatrix} X_g\\ Y_g\\ Z_g\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{g}\textrm{R}_b & _{}^{g}\textrm{t}_b \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_b\\ Y_b\\ Z_b\\ 1 \end{bmatrix} \]
for each pose, the homogeneous transformation between the calibration target frame (the world frame) and the camera frame is recorded using for instance a pose estimation method (PnP) from 2D-3D point correspondences
\[ \begin{bmatrix} X_c\\ Y_c\\ Z_c\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{c}\textrm{R}_w & _{}^{c}\textrm{t}_w \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_w\\ Y_w\\ Z_w\\ 1 \end{bmatrix} \]

The Robot-World/Hand-Eye calibration procedure returns the following homogeneous transformations

\[ \begin{bmatrix} X_w\\ Y_w\\ Z_w\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{w}\textrm{R}_b & _{}^{w}\textrm{t}_b \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_b\\ Y_b\\ Z_b\\ 1 \end{bmatrix} \]

\[ \begin{bmatrix} X_c\\ Y_c\\ Z_c\\ 1 \end{bmatrix} = \begin{bmatrix} _{}^{c}\textrm{R}_g & _{}^{c}\textrm{t}_g \\ 0_{1 \times 3} & 1 \end{bmatrix} \begin{bmatrix} X_g\\ Y_g\\ Z_g\\ 1 \end{bmatrix} \]

This problem is also known as solving the \(\mathbf{A}\mathbf{X}=\mathbf{Z}\mathbf{B}\) equation, with:

\(\mathbf{A} \Leftrightarrow \hspace{0.1em} _{}^{c}\textrm{T}_w\)
\(\mathbf{X} \Leftrightarrow \hspace{0.1em} _{}^{w}\textrm{T}_b\)
\(\mathbf{Z} \Leftrightarrow \hspace{0.1em} _{}^{c}\textrm{T}_g\)
\(\mathbf{B} \Leftrightarrow \hspace{0.1em} _{}^{g}\textrm{T}_b\)

Note: At least 3 measurements are required (input vectors size must be greater or equal to 3).

◆ calibrationMatrixValues() [1/3]

static void OpenCVForUnity.Calib3dModule.Calib3d.calibrationMatrixValues	(	Mat	cameraMatrix,
		in Vec2d	imageSize,
		double	apertureWidth,
		double	apertureHeight,
		double[]	fovx,
		double[]	fovy,
		double[]	focalLength,
		out Vec2d	principalPoint,
		double[]	aspectRatio )

static

Computes useful camera characteristics from the camera intrinsic matrix.

Parameters

cameraMatrix	Input camera intrinsic matrix that can be estimated by calibrateCamera or stereoCalibrate .
imageSize	Input image size in pixels.
apertureWidth	Physical width in mm of the sensor.
apertureHeight	Physical height in mm of the sensor.
fovx	Output field of view in degrees along the horizontal sensor axis.
fovy	Output field of view in degrees along the vertical sensor axis.
focalLength	Focal length of the lens in mm.
principalPoint	Principal point in mm.
aspectRatio	\(f_y/f_x\)

The function computes various useful camera characteristics from the previously estimated camera matrix.

Note: Do keep in mind that the unity measure 'mm' stands for whatever unit of measure one chooses for the chessboard pitch (it can thus be any value).

◆ calibrationMatrixValues() [2/3]

static void OpenCVForUnity.Calib3dModule.Calib3d.calibrationMatrixValues	(	Mat	cameraMatrix,
		in(double width, double height)	imageSize,
		double	apertureWidth,
		double	apertureHeight,
		double[]	fovx,
		double[]	fovy,
		double[]	focalLength,
		out(double x, double y)	principalPoint,
		double[]	aspectRatio )

static

Computes useful camera characteristics from the camera intrinsic matrix.

Parameters

cameraMatrix	Input camera intrinsic matrix that can be estimated by calibrateCamera or stereoCalibrate .
imageSize	Input image size in pixels.
apertureWidth	Physical width in mm of the sensor.
apertureHeight	Physical height in mm of the sensor.
fovx	Output field of view in degrees along the horizontal sensor axis.
fovy	Output field of view in degrees along the vertical sensor axis.
focalLength	Focal length of the lens in mm.
principalPoint	Principal point in mm.
aspectRatio	\(f_y/f_x\)

The function computes various useful camera characteristics from the previously estimated camera matrix.

Note: Do keep in mind that the unity measure 'mm' stands for whatever unit of measure one chooses for the chessboard pitch (it can thus be any value).

◆ calibrationMatrixValues() [3/3]

static void OpenCVForUnity.Calib3dModule.Calib3d.calibrationMatrixValues	(	Mat	cameraMatrix,
		Size	imageSize,
		double	apertureWidth,
		double	apertureHeight,
		double[]	fovx,
		double[]	fovy,
		double[]	focalLength,
		Point	principalPoint,
		double[]	aspectRatio )

static

Computes useful camera characteristics from the camera intrinsic matrix.

Parameters

cameraMatrix	Input camera intrinsic matrix that can be estimated by calibrateCamera or stereoCalibrate .
imageSize	Input image size in pixels.
apertureWidth	Physical width in mm of the sensor.
apertureHeight	Physical height in mm of the sensor.
fovx	Output field of view in degrees along the horizontal sensor axis.
fovy	Output field of view in degrees along the vertical sensor axis.
focalLength	Focal length of the lens in mm.
principalPoint	Principal point in mm.
aspectRatio	\(f_y/f_x\)

The function computes various useful camera characteristics from the previously estimated camera matrix.

Note: Do keep in mind that the unity measure 'mm' stands for whatever unit of measure one chooses for the chessboard pitch (it can thus be any value).

◆ checkChessboard() [1/3]

static bool OpenCVForUnity.Calib3dModule.Calib3d.checkChessboard	(	Mat	img,
		in Vec2d	size )

static

◆ checkChessboard() [2/3]

static bool OpenCVForUnity.Calib3dModule.Calib3d.checkChessboard	(	Mat	img,
		in(double width, double height)	size )

static

◆ checkChessboard() [3/3]

static bool OpenCVForUnity.Calib3dModule.Calib3d.checkChessboard	(	Mat	img,
		Size	size )

static

◆ composeRT() [1/9]

static void OpenCVForUnity.Calib3dModule.Calib3d.composeRT	(	Mat	rvec1,
		Mat	tvec1,
		Mat	rvec2,
		Mat	tvec2,
		Mat	rvec3,
		Mat	tvec3 )

static

Combines two rotation-and-shift transformations.

Parameters

rvec1	First rotation vector.
tvec1	First translation vector.
rvec2	Second rotation vector.
tvec2	Second translation vector.
rvec3	Output rotation vector of the superposition.
tvec3	Output translation vector of the superposition.
dr3dr1	Optional output derivative of rvec3 with regard to rvec1
dr3dt1	Optional output derivative of rvec3 with regard to tvec1
dr3dr2	Optional output derivative of rvec3 with regard to rvec2
dr3dt2	Optional output derivative of rvec3 with regard to tvec2
dt3dr1	Optional output derivative of tvec3 with regard to rvec1
dt3dt1	Optional output derivative of tvec3 with regard to tvec1
dt3dr2	Optional output derivative of tvec3 with regard to rvec2
dt3dt2	Optional output derivative of tvec3 with regard to tvec2

The functions compute:

\[\begin{array}{l} \texttt{rvec3} = \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right ) \\ \texttt{tvec3} = \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \texttt{tvec1} + \texttt{tvec2} \end{array} ,\]

where \(\mathrm{rodrigues}\) denotes a rotation vector to a rotation matrix transformation, and \(\mathrm{rodrigues}^{-1}\) denotes the inverse transformation. See Rodrigues for details.

Also, the functions can compute the derivatives of the output vectors with regards to the input vectors (see matMulDeriv ). The functions are used inside stereoCalibrate but can also be used in your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a function that contains a matrix multiplication.

◆ composeRT() [2/9]

static void OpenCVForUnity.Calib3dModule.Calib3d.composeRT	(	Mat	rvec1,
		Mat	tvec1,
		Mat	rvec2,
		Mat	tvec2,
		Mat	rvec3,
		Mat	tvec3,
		Mat	dr3dr1 )

static

Combines two rotation-and-shift transformations.

Parameters

rvec1	First rotation vector.
tvec1	First translation vector.
rvec2	Second rotation vector.
tvec2	Second translation vector.
rvec3	Output rotation vector of the superposition.
tvec3	Output translation vector of the superposition.
dr3dr1	Optional output derivative of rvec3 with regard to rvec1
dr3dt1	Optional output derivative of rvec3 with regard to tvec1
dr3dr2	Optional output derivative of rvec3 with regard to rvec2
dr3dt2	Optional output derivative of rvec3 with regard to tvec2
dt3dr1	Optional output derivative of tvec3 with regard to rvec1
dt3dt1	Optional output derivative of tvec3 with regard to tvec1
dt3dr2	Optional output derivative of tvec3 with regard to rvec2
dt3dt2	Optional output derivative of tvec3 with regard to tvec2

The functions compute:

\[\begin{array}{l} \texttt{rvec3} = \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right ) \\ \texttt{tvec3} = \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \texttt{tvec1} + \texttt{tvec2} \end{array} ,\]

where \(\mathrm{rodrigues}\) denotes a rotation vector to a rotation matrix transformation, and \(\mathrm{rodrigues}^{-1}\) denotes the inverse transformation. See Rodrigues for details.

Also, the functions can compute the derivatives of the output vectors with regards to the input vectors (see matMulDeriv ). The functions are used inside stereoCalibrate but can also be used in your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a function that contains a matrix multiplication.

◆ composeRT() [3/9]

static void OpenCVForUnity.Calib3dModule.Calib3d.composeRT	(	Mat	rvec1,
		Mat	tvec1,
		Mat	rvec2,
		Mat	tvec2,
		Mat	rvec3,
		Mat	tvec3,
		Mat	dr3dr1,
		Mat	dr3dt1 )

static

Combines two rotation-and-shift transformations.

Parameters

rvec1	First rotation vector.
tvec1	First translation vector.
rvec2	Second rotation vector.
tvec2	Second translation vector.
rvec3	Output rotation vector of the superposition.
tvec3	Output translation vector of the superposition.
dr3dr1	Optional output derivative of rvec3 with regard to rvec1
dr3dt1	Optional output derivative of rvec3 with regard to tvec1
dr3dr2	Optional output derivative of rvec3 with regard to rvec2
dr3dt2	Optional output derivative of rvec3 with regard to tvec2
dt3dr1	Optional output derivative of tvec3 with regard to rvec1
dt3dt1	Optional output derivative of tvec3 with regard to tvec1
dt3dr2	Optional output derivative of tvec3 with regard to rvec2
dt3dt2	Optional output derivative of tvec3 with regard to tvec2

The functions compute:

\[\begin{array}{l} \texttt{rvec3} = \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right ) \\ \texttt{tvec3} = \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \texttt{tvec1} + \texttt{tvec2} \end{array} ,\]

where \(\mathrm{rodrigues}\) denotes a rotation vector to a rotation matrix transformation, and \(\mathrm{rodrigues}^{-1}\) denotes the inverse transformation. See Rodrigues for details.

Also, the functions can compute the derivatives of the output vectors with regards to the input vectors (see matMulDeriv ). The functions are used inside stereoCalibrate but can also be used in your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a function that contains a matrix multiplication.

◆ composeRT() [4/9]

static void OpenCVForUnity.Calib3dModule.Calib3d.composeRT	(	Mat	rvec1,
		Mat	tvec1,
		Mat	rvec2,
		Mat	tvec2,
		Mat	rvec3,
		Mat	tvec3,
		Mat	dr3dr1,
		Mat	dr3dt1,
		Mat	dr3dr2 )

static

Combines two rotation-and-shift transformations.

Parameters

rvec1	First rotation vector.
tvec1	First translation vector.
rvec2	Second rotation vector.
tvec2	Second translation vector.
rvec3	Output rotation vector of the superposition.
tvec3	Output translation vector of the superposition.
dr3dr1	Optional output derivative of rvec3 with regard to rvec1
dr3dt1	Optional output derivative of rvec3 with regard to tvec1
dr3dr2	Optional output derivative of rvec3 with regard to rvec2
dr3dt2	Optional output derivative of rvec3 with regard to tvec2
dt3dr1	Optional output derivative of tvec3 with regard to rvec1
dt3dt1	Optional output derivative of tvec3 with regard to tvec1
dt3dr2	Optional output derivative of tvec3 with regard to rvec2
dt3dt2	Optional output derivative of tvec3 with regard to tvec2

The functions compute:

\[\begin{array}{l} \texttt{rvec3} = \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right ) \\ \texttt{tvec3} = \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \texttt{tvec1} + \texttt{tvec2} \end{array} ,\]

where \(\mathrm{rodrigues}\) denotes a rotation vector to a rotation matrix transformation, and \(\mathrm{rodrigues}^{-1}\) denotes the inverse transformation. See Rodrigues for details.

Also, the functions can compute the derivatives of the output vectors with regards to the input vectors (see matMulDeriv ). The functions are used inside stereoCalibrate but can also be used in your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a function that contains a matrix multiplication.

◆ composeRT() [5/9]

static void OpenCVForUnity.Calib3dModule.Calib3d.composeRT	(	Mat	rvec1,
		Mat	tvec1,
		Mat	rvec2,
		Mat	tvec2,
		Mat	rvec3,
		Mat	tvec3,
		Mat	dr3dr1,
		Mat	dr3dt1,
		Mat	dr3dr2,
		Mat	dr3dt2 )

static

Combines two rotation-and-shift transformations.

Parameters

rvec1	First rotation vector.
tvec1	First translation vector.
rvec2	Second rotation vector.
tvec2	Second translation vector.
rvec3	Output rotation vector of the superposition.
tvec3	Output translation vector of the superposition.
dr3dr1	Optional output derivative of rvec3 with regard to rvec1
dr3dt1	Optional output derivative of rvec3 with regard to tvec1
dr3dr2	Optional output derivative of rvec3 with regard to rvec2
dr3dt2	Optional output derivative of rvec3 with regard to tvec2
dt3dr1	Optional output derivative of tvec3 with regard to rvec1
dt3dt1	Optional output derivative of tvec3 with regard to tvec1
dt3dr2	Optional output derivative of tvec3 with regard to rvec2
dt3dt2	Optional output derivative of tvec3 with regard to tvec2

The functions compute:

\[\begin{array}{l} \texttt{rvec3} = \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right ) \\ \texttt{tvec3} = \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \texttt{tvec1} + \texttt{tvec2} \end{array} ,\]

where \(\mathrm{rodrigues}\) denotes a rotation vector to a rotation matrix transformation, and \(\mathrm{rodrigues}^{-1}\) denotes the inverse transformation. See Rodrigues for details.

Also, the functions can compute the derivatives of the output vectors with regards to the input vectors (see matMulDeriv ). The functions are used inside stereoCalibrate but can also be used in your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a function that contains a matrix multiplication.

◆ composeRT() [6/9]

static void OpenCVForUnity.Calib3dModule.Calib3d.composeRT	(	Mat	rvec1,
		Mat	tvec1,
		Mat	rvec2,
		Mat	tvec2,
		Mat	rvec3,
		Mat	tvec3,
		Mat	dr3dr1,
		Mat	dr3dt1,
		Mat	dr3dr2,
		Mat	dr3dt2,
		Mat	dt3dr1 )

static

Combines two rotation-and-shift transformations.

Parameters

rvec1	First rotation vector.
tvec1	First translation vector.
rvec2	Second rotation vector.
tvec2	Second translation vector.
rvec3	Output rotation vector of the superposition.
tvec3	Output translation vector of the superposition.
dr3dr1	Optional output derivative of rvec3 with regard to rvec1
dr3dt1	Optional output derivative of rvec3 with regard to tvec1
dr3dr2	Optional output derivative of rvec3 with regard to rvec2
dr3dt2	Optional output derivative of rvec3 with regard to tvec2
dt3dr1	Optional output derivative of tvec3 with regard to rvec1
dt3dt1	Optional output derivative of tvec3 with regard to tvec1
dt3dr2	Optional output derivative of tvec3 with regard to rvec2
dt3dt2	Optional output derivative of tvec3 with regard to tvec2

The functions compute:

\[\begin{array}{l} \texttt{rvec3} = \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right ) \\ \texttt{tvec3} = \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \texttt{tvec1} + \texttt{tvec2} \end{array} ,\]

where \(\mathrm{rodrigues}\) denotes a rotation vector to a rotation matrix transformation, and \(\mathrm{rodrigues}^{-1}\) denotes the inverse transformation. See Rodrigues for details.

Also, the functions can compute the derivatives of the output vectors with regards to the input vectors (see matMulDeriv ). The functions are used inside stereoCalibrate but can also be used in your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a function that contains a matrix multiplication.

◆ composeRT() [7/9]

static void OpenCVForUnity.Calib3dModule.Calib3d.composeRT	(	Mat	rvec1,
		Mat	tvec1,
		Mat	rvec2,
		Mat	tvec2,
		Mat	rvec3,
		Mat	tvec3,
		Mat	dr3dr1,
		Mat	dr3dt1,
		Mat	dr3dr2,
		Mat	dr3dt2,
		Mat	dt3dr1,
		Mat	dt3dt1 )

static

Combines two rotation-and-shift transformations.

Parameters

rvec1	First rotation vector.
tvec1	First translation vector.
rvec2	Second rotation vector.
tvec2	Second translation vector.
rvec3	Output rotation vector of the superposition.
tvec3	Output translation vector of the superposition.
dr3dr1	Optional output derivative of rvec3 with regard to rvec1
dr3dt1	Optional output derivative of rvec3 with regard to tvec1
dr3dr2	Optional output derivative of rvec3 with regard to rvec2
dr3dt2	Optional output derivative of rvec3 with regard to tvec2
dt3dr1	Optional output derivative of tvec3 with regard to rvec1
dt3dt1	Optional output derivative of tvec3 with regard to tvec1
dt3dr2	Optional output derivative of tvec3 with regard to rvec2
dt3dt2	Optional output derivative of tvec3 with regard to tvec2

The functions compute:

\[\begin{array}{l} \texttt{rvec3} = \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right ) \\ \texttt{tvec3} = \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \texttt{tvec1} + \texttt{tvec2} \end{array} ,\]

where \(\mathrm{rodrigues}\) denotes a rotation vector to a rotation matrix transformation, and \(\mathrm{rodrigues}^{-1}\) denotes the inverse transformation. See Rodrigues for details.

Also, the functions can compute the derivatives of the output vectors with regards to the input vectors (see matMulDeriv ). The functions are used inside stereoCalibrate but can also be used in your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a function that contains a matrix multiplication.

◆ composeRT() [8/9]

static void OpenCVForUnity.Calib3dModule.Calib3d.composeRT	(	Mat	rvec1,
		Mat	tvec1,
		Mat	rvec2,
		Mat	tvec2,
		Mat	rvec3,
		Mat	tvec3,
		Mat	dr3dr1,
		Mat	dr3dt1,
		Mat	dr3dr2,
		Mat	dr3dt2,
		Mat	dt3dr1,
		Mat	dt3dt1,
		Mat	dt3dr2 )

static

Combines two rotation-and-shift transformations.

Parameters

rvec1	First rotation vector.
tvec1	First translation vector.
rvec2	Second rotation vector.
tvec2	Second translation vector.
rvec3	Output rotation vector of the superposition.
tvec3	Output translation vector of the superposition.
dr3dr1	Optional output derivative of rvec3 with regard to rvec1
dr3dt1	Optional output derivative of rvec3 with regard to tvec1
dr3dr2	Optional output derivative of rvec3 with regard to rvec2
dr3dt2	Optional output derivative of rvec3 with regard to tvec2
dt3dr1	Optional output derivative of tvec3 with regard to rvec1
dt3dt1	Optional output derivative of tvec3 with regard to tvec1
dt3dr2	Optional output derivative of tvec3 with regard to rvec2
dt3dt2	Optional output derivative of tvec3 with regard to tvec2

The functions compute:

\[\begin{array}{l} \texttt{rvec3} = \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right ) \\ \texttt{tvec3} = \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \texttt{tvec1} + \texttt{tvec2} \end{array} ,\]

where \(\mathrm{rodrigues}\) denotes a rotation vector to a rotation matrix transformation, and \(\mathrm{rodrigues}^{-1}\) denotes the inverse transformation. See Rodrigues for details.

Also, the functions can compute the derivatives of the output vectors with regards to the input vectors (see matMulDeriv ). The functions are used inside stereoCalibrate but can also be used in your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a function that contains a matrix multiplication.

◆ composeRT() [9/9]

static void OpenCVForUnity.Calib3dModule.Calib3d.composeRT	(	Mat	rvec1,
		Mat	tvec1,
		Mat	rvec2,
		Mat	tvec2,
		Mat	rvec3,
		Mat	tvec3,
		Mat	dr3dr1,
		Mat	dr3dt1,
		Mat	dr3dr2,
		Mat	dr3dt2,
		Mat	dt3dr1,
		Mat	dt3dt1,
		Mat	dt3dr2,
		Mat	dt3dt2 )

static

Combines two rotation-and-shift transformations.

Parameters

rvec1	First rotation vector.
tvec1	First translation vector.
rvec2	Second rotation vector.
tvec2	Second translation vector.
rvec3	Output rotation vector of the superposition.
tvec3	Output translation vector of the superposition.
dr3dr1	Optional output derivative of rvec3 with regard to rvec1
dr3dt1	Optional output derivative of rvec3 with regard to tvec1
dr3dr2	Optional output derivative of rvec3 with regard to rvec2
dr3dt2	Optional output derivative of rvec3 with regard to tvec2
dt3dr1	Optional output derivative of tvec3 with regard to rvec1
dt3dt1	Optional output derivative of tvec3 with regard to tvec1
dt3dr2	Optional output derivative of tvec3 with regard to rvec2
dt3dt2	Optional output derivative of tvec3 with regard to tvec2

The functions compute:

\[\begin{array}{l} \texttt{rvec3} = \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right ) \\ \texttt{tvec3} = \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \texttt{tvec1} + \texttt{tvec2} \end{array} ,\]

where \(\mathrm{rodrigues}\) denotes a rotation vector to a rotation matrix transformation, and \(\mathrm{rodrigues}^{-1}\) denotes the inverse transformation. See Rodrigues for details.

Also, the functions can compute the derivatives of the output vectors with regards to the input vectors (see matMulDeriv ). The functions are used inside stereoCalibrate but can also be used in your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a function that contains a matrix multiplication.

◆ computeCorrespondEpilines()

static void OpenCVForUnity.Calib3dModule.Calib3d.computeCorrespondEpilines	(	Mat	points,
		int	whichImage,
		Mat	F,
		Mat	lines )

static

For points in an image of a stereo pair, computes the corresponding epilines in the other image.

Parameters

points	Input points. \(N \times 1\) or \(1 \times N\) matrix of type CV_32FC2 or vector<Point2f> .
whichImage	Index of the image (1 or 2) that contains the points .
F	Fundamental matrix that can be estimated using findFundamentalMat or stereoRectify .
lines	Output vector of the epipolar lines corresponding to the points in the other image. Each line \(ax + by + c=0\) is encoded by 3 numbers \((a, b, c)\) .

For every point in one of the two images of a stereo pair, the function finds the equation of the corresponding epipolar line in the other image.

From the fundamental matrix definition (see findFundamentalMat ), line \(l^{(2)}_i\) in the second image for the point \(p^{(1)}_i\) in the first image (when whichImage=1 ) is computed as:

\[l^{(2)}_i = F p^{(1)}_i\]

And vice versa, when whichImage=2, \(l^{(1)}_i\) is computed from \(p^{(2)}_i\) as:

\[l^{(1)}_i = F^T p^{(2)}_i\]

Line coefficients are defined up to a scale. They are normalized so that \(a_i^2+b_i^2=1\) .

◆ convertPointsFromHomogeneous()

static void OpenCVForUnity.Calib3dModule.Calib3d.convertPointsFromHomogeneous	(	Mat	src,
		Mat	dst )

static

Converts points from homogeneous to Euclidean space.

Parameters

src	Input vector of N-dimensional points.
dst	Output vector of N-1-dimensional points.

The function converts points homogeneous to Euclidean space using perspective projection. That is, each point (x1, x2, ... x(n-1), xn) is converted to (x1/xn, x2/xn, ..., x(n-1)/xn). When xn=0, the output point coordinates will be (0,0,0,...).

◆ convertPointsToHomogeneous()

static void OpenCVForUnity.Calib3dModule.Calib3d.convertPointsToHomogeneous	(	Mat	src,
		Mat	dst )

static

Converts points from Euclidean to homogeneous space.

Parameters

src	Input vector of N-dimensional points.
dst	Output vector of N+1-dimensional points.

The function converts points from Euclidean to homogeneous space by appending 1's to the tuple of point coordinates. That is, each point (x1, x2, ..., xn) is converted to (x1, x2, ..., xn, 1).

◆ correctMatches()

static void OpenCVForUnity.Calib3dModule.Calib3d.correctMatches	(	Mat	F,
		Mat	points1,
		Mat	points2,
		Mat	newPoints1,
		Mat	newPoints2 )

static

Refines coordinates of corresponding points.

Parameters

F	3x3 fundamental matrix.
points1	1xN array containing the first set of points.
points2	1xN array containing the second set of points.
newPoints1	The optimized points1.
newPoints2	The optimized points2.

The function implements the Optimal Triangulation Method (see Multiple View Geometry [HartleyZ00] for details). For each given point correspondence points1[i] <-> points2[i], and a fundamental matrix F, it computes the corrected correspondences newPoints1[i] <-> newPoints2[i] that minimize the geometric error \(d(points1[i], newPoints1[i])^2 + d(points2[i],newPoints2[i])^2\) (where \(d(a,b)\) is the geometric distance between points \(a\) and \(b\) ) subject to the epipolar constraint \(newPoints2^T \cdot F \cdot newPoints1 = 0\) .

◆ decomposeEssentialMat()

static void OpenCVForUnity.Calib3dModule.Calib3d.decomposeEssentialMat	(	Mat	E,
		Mat	R1,
		Mat	R2,
		Mat	t )

static

Decompose an essential matrix to possible rotations and translation.

Parameters

E	The input essential matrix.
R1	One possible rotation matrix.
R2	Another possible rotation matrix.
t	One possible translation.

This function decomposes the essential matrix E using svd decomposition [HartleyZ00]. In general, four possible poses exist for the decomposition of E. They are \([R_1, t]\), \([R_1, -t]\), \([R_2, t]\), \([R_2, -t]\).

If E gives the epipolar constraint \([p_2; 1]^T A^{-T} E A^{-1} [p_1; 1] = 0\) between the image points \(p_1\) in the first image and \(p_2\) in second image, then any of the tuples \([R_1, t]\), \([R_1, -t]\), \([R_2, t]\), \([R_2, -t]\) is a change of basis from the first camera's coordinate system to the second camera's coordinate system. However, by decomposing E, one can only get the direction of the translation. For this reason, the translation t is returned with unit length.

◆ decomposeHomographyMat()

static int OpenCVForUnity.Calib3dModule.Calib3d.decomposeHomographyMat	(	Mat	H,
		Mat	K,
		List< Mat >	rotations,
		List< Mat >	translations,
		List< Mat >	normals )

static

Decompose a homography matrix to rotation(s), translation(s) and plane normal(s).

Parameters

H	The input homography matrix between two images.
K	The input camera intrinsic matrix.
rotations	Array of rotation matrices.
translations	Array of translation matrices.
normals	Array of plane normal matrices.

This function extracts relative camera motion between two views of a planar object and returns up to four mathematical solution tuples of rotation, translation, and plane normal. The decomposition of the homography matrix H is described in detail in [Malis2007].

If the homography H, induced by the plane, gives the constraint

\[s_i \vecthree{x'_i}{y'_i}{1} \sim H \vecthree{x_i}{y_i}{1}\]

on the source image points \(p_i\) and the destination image points \(p'_i\), then the tuple of rotations[k] and translations[k] is a change of basis from the source camera's coordinate system to the destination camera's coordinate system. However, by decomposing H, one can only get the translation normalized by the (typically unknown) depth of the scene, i.e. its direction but with normalized length.

If point correspondences are available, at least two solutions may further be invalidated, by applying positive depth constraint, i.e. all points must be in front of the camera.

◆ decomposeProjectionMatrix() [1/5]

static void OpenCVForUnity.Calib3dModule.Calib3d.decomposeProjectionMatrix	(	Mat	projMatrix,
		Mat	cameraMatrix,
		Mat	rotMatrix,
		Mat	transVect )

static

Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.

Parameters

projMatrix	3x4 input projection matrix P.
cameraMatrix	Output 3x3 camera intrinsic matrix \(\cameramatrix{A}\).
rotMatrix	Output 3x3 external rotation matrix R.
transVect	Output 4x1 translation vector T.
rotMatrixX	Optional 3x3 rotation matrix around x-axis.
rotMatrixY	Optional 3x3 rotation matrix around y-axis.
rotMatrixZ	Optional 3x3 rotation matrix around z-axis.
eulerAngles	Optional three-element vector containing three Euler angles of rotation in degrees.

The function computes a decomposition of a projection matrix into a calibration and a rotation matrix and the position of a camera.

It optionally returns three rotation matrices, one for each axis, and three Euler angles that could be used in OpenGL. Note, there is always more than one sequence of rotations about the three principal axes that results in the same orientation of an object, e.g. see [Slabaugh] . Returned three rotation matrices and corresponding three Euler angles are only one of the possible solutions.

The function is based on RQDecomp3x3 .

◆ decomposeProjectionMatrix() [2/5]

static void OpenCVForUnity.Calib3dModule.Calib3d.decomposeProjectionMatrix	(	Mat	projMatrix,
		Mat	cameraMatrix,
		Mat	rotMatrix,
		Mat	transVect,
		Mat	rotMatrixX )

static

Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.

Parameters

projMatrix	3x4 input projection matrix P.
cameraMatrix	Output 3x3 camera intrinsic matrix \(\cameramatrix{A}\).
rotMatrix	Output 3x3 external rotation matrix R.
transVect	Output 4x1 translation vector T.
rotMatrixX	Optional 3x3 rotation matrix around x-axis.
rotMatrixY	Optional 3x3 rotation matrix around y-axis.
rotMatrixZ	Optional 3x3 rotation matrix around z-axis.
eulerAngles	Optional three-element vector containing three Euler angles of rotation in degrees.

The function computes a decomposition of a projection matrix into a calibration and a rotation matrix and the position of a camera.

It optionally returns three rotation matrices, one for each axis, and three Euler angles that could be used in OpenGL. Note, there is always more than one sequence of rotations about the three principal axes that results in the same orientation of an object, e.g. see [Slabaugh] . Returned three rotation matrices and corresponding three Euler angles are only one of the possible solutions.

The function is based on RQDecomp3x3 .

◆ decomposeProjectionMatrix() [3/5]

static void OpenCVForUnity.Calib3dModule.Calib3d.decomposeProjectionMatrix	(	Mat	projMatrix,
		Mat	cameraMatrix,
		Mat	rotMatrix,
		Mat	transVect,
		Mat	rotMatrixX,
		Mat	rotMatrixY )

static

Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.

Parameters

projMatrix	3x4 input projection matrix P.
cameraMatrix	Output 3x3 camera intrinsic matrix \(\cameramatrix{A}\).
rotMatrix	Output 3x3 external rotation matrix R.
transVect	Output 4x1 translation vector T.
rotMatrixX	Optional 3x3 rotation matrix around x-axis.
rotMatrixY	Optional 3x3 rotation matrix around y-axis.
rotMatrixZ	Optional 3x3 rotation matrix around z-axis.
eulerAngles	Optional three-element vector containing three Euler angles of rotation in degrees.

The function computes a decomposition of a projection matrix into a calibration and a rotation matrix and the position of a camera.

It optionally returns three rotation matrices, one for each axis, and three Euler angles that could be used in OpenGL. Note, there is always more than one sequence of rotations about the three principal axes that results in the same orientation of an object, e.g. see [Slabaugh] . Returned three rotation matrices and corresponding three Euler angles are only one of the possible solutions.

The function is based on RQDecomp3x3 .

◆ decomposeProjectionMatrix() [4/5]

static void OpenCVForUnity.Calib3dModule.Calib3d.decomposeProjectionMatrix	(	Mat	projMatrix,
		Mat	cameraMatrix,
		Mat	rotMatrix,
		Mat	transVect,
		Mat	rotMatrixX,
		Mat	rotMatrixY,
		Mat	rotMatrixZ )

static

Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.

Parameters

projMatrix	3x4 input projection matrix P.
cameraMatrix	Output 3x3 camera intrinsic matrix \(\cameramatrix{A}\).
rotMatrix	Output 3x3 external rotation matrix R.
transVect	Output 4x1 translation vector T.
rotMatrixX	Optional 3x3 rotation matrix around x-axis.
rotMatrixY	Optional 3x3 rotation matrix around y-axis.
rotMatrixZ	Optional 3x3 rotation matrix around z-axis.
eulerAngles	Optional three-element vector containing three Euler angles of rotation in degrees.

The function computes a decomposition of a projection matrix into a calibration and a rotation matrix and the position of a camera.

It optionally returns three rotation matrices, one for each axis, and three Euler angles that could be used in OpenGL. Note, there is always more than one sequence of rotations about the three principal axes that results in the same orientation of an object, e.g. see [Slabaugh] . Returned three rotation matrices and corresponding three Euler angles are only one of the possible solutions.

The function is based on RQDecomp3x3 .

◆ decomposeProjectionMatrix() [5/5]

static void OpenCVForUnity.Calib3dModule.Calib3d.decomposeProjectionMatrix	(	Mat	projMatrix,
		Mat	cameraMatrix,
		Mat	rotMatrix,
		Mat	transVect,
		Mat	rotMatrixX,
		Mat	rotMatrixY,
		Mat	rotMatrixZ,
		Mat	eulerAngles )

static

Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.

Parameters

projMatrix	3x4 input projection matrix P.
cameraMatrix	Output 3x3 camera intrinsic matrix \(\cameramatrix{A}\).
rotMatrix	Output 3x3 external rotation matrix R.
transVect	Output 4x1 translation vector T.
rotMatrixX	Optional 3x3 rotation matrix around x-axis.
rotMatrixY	Optional 3x3 rotation matrix around y-axis.
rotMatrixZ	Optional 3x3 rotation matrix around z-axis.
eulerAngles	Optional three-element vector containing three Euler angles of rotation in degrees.

The function computes a decomposition of a projection matrix into a calibration and a rotation matrix and the position of a camera.

It optionally returns three rotation matrices, one for each axis, and three Euler angles that could be used in OpenGL. Note, there is always more than one sequence of rotations about the three principal axes that results in the same orientation of an object, e.g. see [Slabaugh] . Returned three rotation matrices and corresponding three Euler angles are only one of the possible solutions.

The function is based on RQDecomp3x3 .

◆ drawChessboardCorners() [1/3]

static void OpenCVForUnity.Calib3dModule.Calib3d.drawChessboardCorners	(	Mat	image,
		in Vec2d	patternSize,
		MatOfPoint2f	corners,
		bool	patternWasFound )

static

Renders the detected chessboard corners.

Parameters

image	Destination image. It must be an 8-bit color image.
patternSize	Number of inner corners per a chessboard row and column (patternSize = cv::Size(points_per_row,points_per_column)).
corners	Array of detected corners, the output of findChessboardCorners.
patternWasFound	Parameter indicating whether the complete board was found or not. The return value of findChessboardCorners should be passed here.

The function draws individual chessboard corners detected either as red circles if the board was not found, or as colored corners connected with lines if the board was found.

◆ drawChessboardCorners() [2/3]

static void OpenCVForUnity.Calib3dModule.Calib3d.drawChessboardCorners	(	Mat	image,
		in(double width, double height)	patternSize,
		MatOfPoint2f	corners,
		bool	patternWasFound )

static

Renders the detected chessboard corners.

Parameters

image	Destination image. It must be an 8-bit color image.
patternSize	Number of inner corners per a chessboard row and column (patternSize = cv::Size(points_per_row,points_per_column)).
corners	Array of detected corners, the output of findChessboardCorners.
patternWasFound	Parameter indicating whether the complete board was found or not. The return value of findChessboardCorners should be passed here.

The function draws individual chessboard corners detected either as red circles if the board was not found, or as colored corners connected with lines if the board was found.

◆ drawChessboardCorners() [3/3]

static void OpenCVForUnity.Calib3dModule.Calib3d.drawChessboardCorners	(	Mat	image,
		Size	patternSize,
		MatOfPoint2f	corners,
		bool	patternWasFound )

static

Renders the detected chessboard corners.

Parameters

image	Destination image. It must be an 8-bit color image.
patternSize	Number of inner corners per a chessboard row and column (patternSize = cv::Size(points_per_row,points_per_column)).
corners	Array of detected corners, the output of findChessboardCorners.
patternWasFound	Parameter indicating whether the complete board was found or not. The return value of findChessboardCorners should be passed here.

The function draws individual chessboard corners detected either as red circles if the board was not found, or as colored corners connected with lines if the board was found.

◆ drawFrameAxes() [1/2]

static void OpenCVForUnity.Calib3dModule.Calib3d.drawFrameAxes	(	Mat	image,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		Mat	rvec,
		Mat	tvec,
		float	length )

static

Draw axes of the world/object coordinate system from pose estimation.

See also: solvePnP

Parameters

image	Input/output image. It must have 1 or 3 channels. The number of channels is not altered.
cameraMatrix	Input 3x3 floating-point matrix of camera intrinsic parameters. \(\cameramatrix{A}\)
distCoeffs	Input vector of distortion coefficients \(\distcoeffs\). If the vector is empty, the zero distortion coefficients are assumed.
rvec	Rotation vector (see Rodrigues ) that, together with tvec, brings points from the model coordinate system to the camera coordinate system.
tvec	Translation vector.
length	Length of the painted axes in the same unit than tvec (usually in meters).
thickness	Line thickness of the painted axes.

This function draws the axes of the world/object coordinate system w.r.t. to the camera frame. OX is drawn in red, OY in green and OZ in blue.

◆ drawFrameAxes() [2/2]

static void OpenCVForUnity.Calib3dModule.Calib3d.drawFrameAxes	(	Mat	image,
		Mat	cameraMatrix,
		Mat	distCoeffs,
		Mat	rvec,
		Mat	tvec,
		float	length,
		int	thickness )

static

Draw axes of the world/object coordinate system from pose estimation.

See also: solvePnP

Parameters

image	Input/output image. It must have 1 or 3 channels. The number of channels is not altered.
cameraMatrix	Input 3x3 floating-point matrix of camera intrinsic parameters. \(\cameramatrix{A}\)
distCoeffs	Input vector of distortion coefficients \(\distcoeffs\). If the vector is empty, the zero distortion coefficients are assumed.
rvec	Rotation vector (see Rodrigues ) that, together with tvec, brings points from the model coordinate system to the camera coordinate system.
tvec	Translation vector.
length	Length of the painted axes in the same unit than tvec (usually in meters).
thickness	Line thickness of the painted axes.

This function draws the axes of the world/object coordinate system w.r.t. to the camera frame. OX is drawn in red, OY in green and OZ in blue.

◆ estimateAffine2D() [1/8]

static Mat OpenCVForUnity.Calib3dModule.Calib3d.estimateAffine2D	(	Mat	from,
		Mat	to )

static

Computes an optimal affine transformation between two 2D point sets.

It computes

\[ \begin{bmatrix} x\\ y\\ \end{bmatrix} = \begin{bmatrix} a_{11} & a_{12}\\ a_{21} & a_{22}\\ \end{bmatrix} \begin{bmatrix} X\\ Y\\ \end{bmatrix} + \begin{bmatrix} b_1\\ b_2\\ \end{bmatrix} \]

Parameters

from	First input 2D point set containing \((X,Y)\).
to	Second input 2D point set containing \((x,y)\).
inliers	Output vector indicating which points are inliers (1-inlier, 0-outlier).
method	Robust method used to compute transformation. The following methods are possible: RANSAC - RANSAC-based robust method LMEDS - Least-Median robust method RANSAC is the default method.
ransacReprojThreshold	Maximum reprojection error in the RANSAC algorithm to consider a point as an inlier. Applies only to RANSAC.
maxIters	The maximum number of robust method iterations.
confidence	Confidence level, between 0 and 1, for the estimated transformation. Anything between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation.
refineIters	Maximum number of iterations of refining algorithm (Levenberg-Marquardt). Passing 0 will disable refining, so the output matrix will be output of robust method.

Returns: Output 2D affine transformation matrix \(2 \times 3\) or empty matrix if transformation could not be estimated. The returned matrix has the following form:
\[ \begin{bmatrix} a_{11} & a_{12} & b_1\\ a_{21} & a_{22} & b_2\\ \end{bmatrix} \]

The function estimates an optimal 2D affine transformation between two 2D point sets using the selected robust algorithm.

The computed transformation is then refined further (using only inliers) with the Levenberg-Marquardt method to reduce the re-projection error even more.

Note: The RANSAC method can handle practically any ratio of outliers but needs a threshold to distinguish inliers from outliers. The method LMeDS does not need any threshold but it works correctly only when there are more than 50% of inliers.

See also: estimateAffinePartial2D, getAffineTransform

◆ estimateAffine2D() [2/8]

static Mat OpenCVForUnity.Calib3dModule.Calib3d.estimateAffine2D	(	Mat	from,
		Mat	to,
		Mat	inliers )

static

Computes an optimal affine transformation between two 2D point sets.

It computes

\[ \begin{bmatrix} x\\ y\\ \end{bmatrix} = \begin{bmatrix} a_{11} & a_{12}\\ a_{21} & a_{22}\\ \end{bmatrix} \begin{bmatrix} X\\ Y\\ \end{bmatrix} + \begin{bmatrix} b_1\\ b_2\\ \end{bmatrix} \]

Parameters

from	First input 2D point set containing \((X,Y)\).
to	Second input 2D point set containing \((x,y)\).
inliers	Output vector indicating which points are inliers (1-inlier, 0-outlier).
method	Robust method used to compute transformation. The following methods are possible: RANSAC - RANSAC-based robust method LMEDS - Least-Median robust method RANSAC is the default method.
ransacReprojThreshold	Maximum reprojection error in the RANSAC algorithm to consider a point as an inlier. Applies only to RANSAC.
maxIters	The maximum number of robust method iterations.
confidence	Confidence level, between 0 and 1, for the estimated transformation. Anything between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation.
refineIters	Maximum number of iterations of refining algorithm (Levenberg-Marquardt). Passing 0 will disable refining, so the output matrix will be output of robust method.

Returns: Output 2D affine transformation matrix \(2 \times 3\) or empty matrix if transformation could not be estimated. The returned matrix has the following form:

Static Public Member Functions

Static Public Attributes

Member Function Documentation

◆ calibrateCamera() [1/9]

◆ calibrateCamera() [2/9]

◆ calibrateCamera() [3/9]

◆ calibrateCamera() [4/9]

◆ calibrateCamera() [5/9]

◆ calibrateCamera() [6/9]

◆ calibrateCamera() [7/9]

◆ calibrateCamera() [8/9]

◆ calibrateCamera() [9/9]

◆ calibrateCameraExtended() [1/9]

◆ calibrateCameraExtended() [2/9]

◆ calibrateCameraExtended() [3/9]

◆ calibrateCameraExtended() [4/9]

◆ calibrateCameraExtended() [5/9]

◆ calibrateCameraExtended() [6/9]

◆ calibrateCameraExtended() [7/9]

◆ calibrateCameraExtended() [8/9]

◆ calibrateCameraExtended() [9/9]

◆ calibrateCameraRO() [1/9]

◆ calibrateCameraRO() [2/9]

◆ calibrateCameraRO() [3/9]

◆ calibrateCameraRO() [4/9]

◆ calibrateCameraRO() [5/9]

◆ calibrateCameraRO() [6/9]

◆ calibrateCameraRO() [7/9]

◆ calibrateCameraRO() [8/9]

◆ calibrateCameraRO() [9/9]

◆ calibrateCameraROExtended() [1/9]

◆ calibrateCameraROExtended() [2/9]

◆ calibrateCameraROExtended() [3/9]

◆ calibrateCameraROExtended() [4/9]

◆ calibrateCameraROExtended() [5/9]

◆ calibrateCameraROExtended() [6/9]

◆ calibrateCameraROExtended() [7/9]

◆ calibrateCameraROExtended() [8/9]

◆ calibrateCameraROExtended() [9/9]

◆ calibrateHandEye() [1/2]

◆ calibrateHandEye() [2/2]

◆ calibrateRobotWorldHandEye() [1/2]

◆ calibrateRobotWorldHandEye() [2/2]

◆ calibrationMatrixValues() [1/3]

◆ calibrationMatrixValues() [2/3]

◆ calibrationMatrixValues() [3/3]

◆ checkChessboard() [1/3]

◆ checkChessboard() [2/3]

◆ checkChessboard() [3/3]

◆ composeRT() [1/9]

◆ composeRT() [2/9]

◆ composeRT() [3/9]

◆ composeRT() [4/9]

◆ composeRT() [5/9]

◆ composeRT() [6/9]

◆ composeRT() [7/9]

◆ composeRT() [8/9]

◆ composeRT() [9/9]

◆ computeCorrespondEpilines()

◆ convertPointsFromHomogeneous()

◆ convertPointsToHomogeneous()

◆ correctMatches()

◆ decomposeEssentialMat()

◆ decomposeHomographyMat()

◆ decomposeProjectionMatrix() [1/5]

◆ decomposeProjectionMatrix() [2/5]

◆ decomposeProjectionMatrix() [3/5]

◆ decomposeProjectionMatrix() [4/5]

◆ decomposeProjectionMatrix() [5/5]

◆ drawChessboardCorners() [1/3]

◆ drawChessboardCorners() [2/3]

◆ drawChessboardCorners() [3/3]

◆ drawFrameAxes() [1/2]

◆ drawFrameAxes() [2/2]

◆ estimateAffine2D() [1/8]

◆ estimateAffine2D() [2/8]