OpenCV for Unity 2.6.5
Enox Software / Please refer to OpenCV official document ( http://docs.opencv.org/4.10.0/index.html ) for the details of the argument of the method.
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OpenCVForUnity.Calib3dModule.Calib3d Class Reference

Static Public Member Functions

static double calibrateCamera (List< Mat > objectPoints, List< Mat > imagePoints, in Vec2d imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs)
 
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, int flags, in Vec3d 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)
 
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, int flags, in(double type, double maxCount, double epsilon) criteria)
 
static double calibrateCamera (List< Mat > objectPoints, List< Mat > imagePoints, Size imageSize, Mat cameraMatrix, Mat distCoeffs, List< Mat > rvecs, List< Mat > tvecs)
 
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, int flags, TermCriteria criteria)
 
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 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, 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(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 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, 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, 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 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, int flags, TermCriteria criteria)
 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)
 
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, int flags, in Vec3d 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)
 
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, int flags, in(double type, double maxCount, double epsilon) 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)
 
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, int flags, TermCriteria criteria)
 
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 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, 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(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 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, 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, 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 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, int flags, TermCriteria criteria)
 Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
 
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 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 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 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 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 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 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 bool checkChessboard (Mat img, in Vec2d size)
 
static bool checkChessboard (Mat img, in(double width, double height) size)
 
static bool checkChessboard (Mat img, Size size)
 
static void composeRT (Mat rvec1, Mat tvec1, Mat rvec2, Mat tvec2, Mat rvec3, Mat tvec3)
 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, 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, 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, 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, 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, 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, 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, Mat dt3dr2, Mat dt3dt2)
 Combines two rotation-and-shift transformations.
 
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 convertPointsFromHomogeneous (Mat src, Mat dst)
 Converts points from homogeneous to Euclidean space.
 
static void convertPointsToHomogeneous (Mat src, Mat dst)
 Converts points from Euclidean to homogeneous space.
 
static void correctMatches (Mat F, Mat points1, Mat points2, Mat newPoints1, Mat newPoints2)
 Refines coordinates of corresponding points.
 
static void decomposeEssentialMat (Mat E, Mat R1, Mat R2, Mat t)
 Decompose an essential matrix to possible rotations and translation.
 
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 decomposeProjectionMatrix (Mat projMatrix, Mat cameraMatrix, Mat rotMatrix, Mat transVect)
 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, 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, 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, Mat rotMatrixZ, Mat eulerAngles)
 Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.
 
static void drawChessboardCorners (Mat image, in Vec2d patternSize, MatOfPoint2f corners, bool patternWasFound)
 Renders the detected chessboard corners.
 
static void drawChessboardCorners (Mat image, in(double width, double height) patternSize, MatOfPoint2f corners, bool patternWasFound)
 Renders the detected chessboard corners.
 
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)
 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, int thickness)
 Draw axes of the world/object coordinate system from pose estimation.
 
static Mat estimateAffine2D (Mat from, Mat to)
 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, Mat inliers, int method)
 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, 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, 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, double confidence, long refineIters)
 Computes an optimal affine transformation between two 2D point sets.
 
static Mat estimateAffine2D (Mat pts1, Mat pts2, Mat inliers, UsacParams _params)
 
static Mat estimateAffine3D (Mat src, Mat dst)
 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, double[] scale, bool force_rotation)
 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 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, double ransacThreshold, double confidence)
 Computes an optimal affine transformation between two 3D 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 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, 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, 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, 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, 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, double confidence, long refineIters)
 Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.
 
static Scalar estimateChessboardSharpness (Mat image, Size patternSize, Mat corners)
 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, float rise_distance, bool vertical)
 Estimates the sharpness of a detected chessboard.
 
static Scalar estimateChessboardSharpness (Mat image, Size patternSize, Mat corners, float rise_distance, bool vertical, Mat sharpness)
 Estimates the sharpness of a detected chessboard.
 
static double double double double v3 estimateChessboardSharpnessAsValueTuple (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)
 
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, bool vertical, Mat sharpness)
 
static Vec4d estimateChessboardSharpnessAsVec4d (Mat image, in Vec2d patternSize, Mat corners)
 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, 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, bool vertical, Mat sharpness)
 Estimates the sharpness of a detected chessboard.
 
static int estimateTranslation3D (Mat src, Mat dst, Mat _out, Mat inliers)
 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, double ransacThreshold, double confidence)
 Computes an optimal translation between two 3D point sets.
 
static void filterHomographyDecompByVisibleRefpoints (List< Mat > rotations, List< Mat > normals, Mat beforePoints, Mat afterPoints, Mat possibleSolutions)
 Filters homography decompositions based on additional information.
 
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 filterSpeckles (Mat img, double newVal, int maxSpeckleSize, double maxDiff)
 Filters off small noise blobs (speckles) in the disparity map.
 
static void filterSpeckles (Mat img, double newVal, int maxSpeckleSize, double maxDiff, Mat buf)
 Filters off small noise blobs (speckles) in the disparity map.
 
static bool find4QuadCornerSubpix (Mat img, Mat corners, in Vec2d region_size)
 
static bool find4QuadCornerSubpix (Mat img, Mat corners, in(double width, double height) region_size)
 
static bool find4QuadCornerSubpix (Mat img, Mat corners, Size region_size)
 
static bool findChessboardCorners (Mat image, in Vec2d patternSize, MatOfPoint2f corners)
 Finds the positions of internal corners of the chessboard.
 
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(double width, double height) patternSize, MatOfPoint2f corners)
 Finds the positions of internal corners of the chessboard.
 
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, Size patternSize, MatOfPoint2f corners)
 Finds the positions of internal corners of the chessboard.
 
static bool findChessboardCorners (Mat image, Size patternSize, MatOfPoint2f corners, int flags)
 Finds the positions of internal corners of the chessboard.
 
static bool findChessboardCornersSB (Mat image, in Vec2d patternSize, Mat corners)
 
static bool findChessboardCornersSB (Mat image, in Vec2d patternSize, Mat corners, int flags)
 
static bool findChessboardCornersSB (Mat image, in(double width, double height) patternSize, Mat corners)
 
static bool findChessboardCornersSB (Mat image, in(double width, double height) patternSize, Mat corners, int flags)
 
static bool findChessboardCornersSB (Mat image, Size patternSize, Mat corners)
 
static bool findChessboardCornersSB (Mat image, Size patternSize, Mat corners, int flags)
 
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 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 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 findCirclesGrid (Mat image, in Vec2d patternSize, Mat centers)
 
static bool findCirclesGrid (Mat image, in Vec2d patternSize, Mat centers, int flags)
 
static bool findCirclesGrid (Mat image, in(double width, double height) patternSize, Mat centers)
 
static bool findCirclesGrid (Mat image, in(double width, double height) patternSize, Mat centers, int flags)
 
static bool findCirclesGrid (Mat image, Size patternSize, Mat centers)
 
static bool findCirclesGrid (Mat image, Size patternSize, Mat centers, int flags)
 
static Mat findEssentialMat (Mat points1, Mat points2)
 
static Mat findEssentialMat (Mat points1, Mat points2, double focal)
 
static Mat findEssentialMat (Mat points1, Mat points2, double focal, in Vec2d pp)
 
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, int method, double prob)
 
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, double threshold, int maxIters)
 
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(double x, double y) pp)
 
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, int method, double prob)
 
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, 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, int maxIters, Mat mask)
 
static Mat findEssentialMat (Mat points1, Mat points2, double focal, Point pp)
 
static Mat findEssentialMat (Mat points1, Mat points2, double focal, Point pp, int method)
 
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, double prob, double threshold)
 
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, int maxIters, Mat mask)
 
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, Mat cameraMatrix, int method)
 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, 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, 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, int maxIters, Mat mask)
 Calculates an essential matrix from the corresponding points in two images.
 
static Mat findEssentialMat (Mat points1, Mat points2, Mat cameraMatrix1, Mat cameraMatrix2, Mat dist_coeff1, Mat dist_coeff2, Mat mask, UsacParams _params)
 
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 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, 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, 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, double threshold, Mat mask)
 Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
 
static Mat findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2)
 
static Mat findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2, int method)
 
static Mat findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold)
 
static Mat findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2, int method, double ransacReprojThreshold, double confidence)
 
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, 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, Mat mask)
 
static Mat findFundamentalMat (MatOfPoint2f points1, MatOfPoint2f points2, Mat mask, UsacParams _params)
 
static Mat findHomography (MatOfPoint2f srcPoints, MatOfPoint2f dstPoints)
 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, int method, double ransacReprojThreshold)
 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, Mat mask, int maxIters)
 Finds a perspective transformation between two planes.
 
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, Mat mask, UsacParams _params)
 
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 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, int flags, in Vec3d 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)
 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, int flags, in(double type, double maxCount, double epsilon) 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)
 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, int flags, TermCriteria criteria)
 Performs camera calibration.
 
static void fisheye_distortPoints (Mat undistorted, Mat distorted, Mat K, Mat D)
 Distorts 2D points using fisheye model.
 
static void fisheye_distortPoints (Mat undistorted, Mat distorted, Mat K, Mat D, double alpha)
 Distorts 2D points using fisheye model.
 
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 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, 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, 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(double width, double height) image_size, Mat R, Mat P)
 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, 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, 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, Size image_size, Mat R, Mat P)
 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, 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, Size new_size, double fov_scale)
 Estimates new camera intrinsic matrix for undistortion or rectification.
 
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_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_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_projectPoints (Mat objectPoints, Mat imagePoints, Mat rvec, Mat tvec, Mat K, Mat D)
 
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, double alpha, Mat jacobian)
 
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 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, 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, int flags, in Vec3d 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, in(double type, double maxCount, double epsilon) 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, TermCriteria criteria)
 Finds an object pose from 3D-2D point correspondences for fisheye camera moodel.
 
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 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, 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, 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, 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, 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(double width, double height) imageSize, Mat R, Mat T)
 
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, 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, 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, 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, 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, Size imageSize, Mat R, Mat T)
 
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, 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, 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, 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, int flags, TermCriteria criteria)
 Performs stereo 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)
 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, 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, 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)
 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, 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, 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)
 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, 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, double balance, double fov_scale)
 Stereo rectification for fisheye camera model.
 
static void fisheye_undistortImage (Mat distorted, Mat undistorted, Mat K, Mat D)
 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, Mat Knew, in Vec2d 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, in(double width, double height) 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, Size new_size)
 Transforms an image to compensate for fisheye lens distortion.
 
static void fisheye_undistortPoints (Mat distorted, Mat undistorted, Mat K, Mat D)
 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, Mat R, Mat P)
 Undistorts 2D points using fisheye model.
 
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_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_undistortPoints (Mat distorted, Mat undistorted, Mat K, Mat D, Mat R, Mat P, TermCriteria criteria)
 Undistorts 2D points using fisheye model.
 
static Mat getDefaultNewCameraMatrix (Mat cameraMatrix)
 Returns the default new camera matrix.
 
static Mat getDefaultNewCameraMatrix (Mat cameraMatrix, in Vec2d imgsize)
 Returns the default new camera matrix.
 
static Mat getDefaultNewCameraMatrix (Mat cameraMatrix, in Vec2d 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 Mat getDefaultNewCameraMatrix (Mat cameraMatrix, in(double width, double height) 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, Size imgsize, bool centerPrincipalPoint)
 Returns the default new camera matrix.
 
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 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, 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, 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(double width, double height) imageSize, double alpha)
 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, 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, 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, Size imageSize, double alpha)
 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, 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, Rect validPixROI, bool centerPrincipalPoint)
 Returns the new camera intrinsic matrix based on the free scaling parameter.
 
static Rect getValidDisparityROI (Rect roi1, Rect roi2, int minDisparity, int numberOfDisparities, int blockSize)
 
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 Vec4i getValidDisparityROIAsVec4i (in Vec4i roi1, Vec4i roi2, int minDisparity, int numberOfDisparities, int blockSize)
 
static Mat initCameraMatrix2D (List< MatOfPoint3f > objectPoints, List< MatOfPoint2f > imagePoints, in Vec2d imageSize)
 Finds an initial camera intrinsic matrix from 3D-2D point correspondences.
 
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(double width, double height) imageSize)
 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, 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 Mat initCameraMatrix2D (List< MatOfPoint3f > objectPoints, List< MatOfPoint2f > imagePoints, Size imageSize, double aspectRatio)
 Finds an initial camera intrinsic matrix from 3D-2D point correspondences.
 
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 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 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 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 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 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 matMulDeriv (Mat A, Mat B, Mat dABdA, Mat dABdB)
 Computes partial derivatives of the matrix product for each multiplied matrix.
 
static void projectPoints (MatOfPoint3f objectPoints, Mat rvec, Mat tvec, Mat cameraMatrix, MatOfDouble distCoeffs, MatOfPoint2f imagePoints)
 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, Mat jacobian, double aspectRatio)
 Projects 3D points to an image plane.
 
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 cameraMatrix, Mat R, Mat t, double distanceThresh)
 
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, Mat mask, Mat triangulatedPoints)
 
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 R, Mat t)
 
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, 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(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, Point pp)
 
static int recoverPose (Mat E, Mat points1, Mat points2, Mat R, Mat t, double focal, Point pp, Mat mask)
 
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 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, 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, 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, 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 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 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 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 void reprojectImageTo3D (Mat disparity, Mat _3dImage, Mat Q)
 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, bool handleMissingValues, int ddepth)
 Reprojects a disparity image to 3D space.
 
static void Rodrigues (Mat src, Mat dst)
 Converts a rotation matrix to a rotation vector or vice versa.
 
static void Rodrigues (Mat src, Mat dst, Mat jacobian)
 Converts a rotation matrix to a rotation vector or vice versa.
 
static double[] RQDecomp3x3 (Mat src, Mat mtxR, Mat mtxQ)
 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, Mat Qx, Mat Qy)
 Computes an RQ decomposition of 3x3 matrices.
 
static double[] RQDecomp3x3 (Mat src, Mat mtxR, Mat mtxQ, Mat Qx, Mat Qy, Mat Qz)
 Computes an RQ decomposition of 3x3 matrices.
 
static double sampsonDistance (Mat pt1, Mat pt2, Mat F)
 Calculates the Sampson Distance between two points.
 
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 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 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, 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)
 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, 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, 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, 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, Mat tvec, Mat reprojectionError)
 Finds an object pose from 3D-2D point correspondences.
 
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, 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, 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, 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, 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, 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, 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, Mat inliers)
 
static bool solvePnPRansac (MatOfPoint3f objectPoints, MatOfPoint2f imagePoints, Mat cameraMatrix, MatOfDouble distCoeffs, Mat rvec, Mat tvec, Mat inliers, UsacParams _params)
 
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 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 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 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 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 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 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(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, 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, 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 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, 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, 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)
 
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, 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(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, 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, 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)
 
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, 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, 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, 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, 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)
 
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, int flags, TermCriteria criteria)
 
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 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, 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(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 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, 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, 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 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, 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 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 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, 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, 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, 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, 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(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 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, 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, 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, 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, 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, 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 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, 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, 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, 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, Rect validPixROI1, Rect validPixROI2)
 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)
 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, 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 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, Size imgSize, Mat H1, Mat H2)
 Computes a rectification transform for an uncalibrated 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 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 undistort (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs)
 Transforms an image to compensate for lens distortion.
 
static void undistort (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, Mat newCameraMatrix)
 Transforms an image to compensate for lens distortion.
 
static void undistortImagePoints (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs)
 Compute undistorted image points position.
 
static void undistortImagePoints (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, in Vec3d arg1)
 Compute undistorted image points position.
 
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 undistortImagePoints (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, TermCriteria arg1)
 Compute undistorted image points position.
 
static void undistortPoints (MatOfPoint2f src, MatOfPoint2f dst, Mat cameraMatrix, Mat distCoeffs)
 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, Mat R, Mat P)
 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, in Vec3d criteria)
 
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 undistortPointsIter (Mat src, Mat dst, Mat cameraMatrix, Mat distCoeffs, Mat R, Mat P, TermCriteria criteria)
 
static void validateDisparity (Mat disparity, Mat cost, int minDisparity, int numberOfDisparities)
 
static void validateDisparity (Mat disparity, Mat cost, int minDisparity, int numberOfDisparities, int disp12MaxDisp)
 

Static Public Attributes

const int CALIB_CB_ACCURACY = 32
 
const int CALIB_CB_ADAPTIVE_THRESH = 1
 
const int CALIB_CB_ASYMMETRIC_GRID = 2
 
const int CALIB_CB_CLUSTERING = 4
 
const int CALIB_CB_EXHAUSTIVE = 16
 
const int CALIB_CB_FAST_CHECK = 8
 
const int CALIB_CB_FILTER_QUADS = 4
 
const int CALIB_CB_LARGER = 64
 
const int CALIB_CB_MARKER = 128
 
const int CALIB_CB_NORMALIZE_IMAGE = 2
 
const int CALIB_CB_PLAIN = 256
 
const int CALIB_CB_SYMMETRIC_GRID = 1
 
const int CALIB_FIX_ASPECT_RATIO = 0x00002
 
const int CALIB_FIX_FOCAL_LENGTH = 0x00010
 
const int CALIB_FIX_INTRINSIC = 0x00100
 
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_FIX_PRINCIPAL_POINT = 0x00004
 
const int CALIB_FIX_S1_S2_S3_S4 = 0x10000
 
const int CALIB_FIX_TANGENT_DIST = 0x200000
 
const int CALIB_FIX_TAUX_TAUY = 0x80000
 
const int CALIB_HAND_EYE_ANDREFF = 3
 
const int CALIB_HAND_EYE_DANIILIDIS = 4
 
const int CALIB_HAND_EYE_HORAUD = 2
 
const int CALIB_HAND_EYE_PARK = 1
 
const int CALIB_HAND_EYE_TSAI = 0
 
const int CALIB_NINTRINSIC = 18
 
const int CALIB_RATIONAL_MODEL = 0x04000
 
const int CALIB_ROBOT_WORLD_HAND_EYE_LI = 1
 
const int CALIB_ROBOT_WORLD_HAND_EYE_SHAH = 0
 
const int CALIB_SAME_FOCAL_LENGTH = 0x00200
 
const int CALIB_THIN_PRISM_MODEL = 0x08000
 
const int CALIB_TILTED_MODEL = 0x40000
 
const int CALIB_USE_EXTRINSIC_GUESS = (1 << 22)
 
const int CALIB_USE_INTRINSIC_GUESS = 0x00001
 
const int CALIB_USE_LU = (1 << 17)
 
const int CALIB_USE_QR = 0x100000
 
const int CALIB_ZERO_DISPARITY = 0x00400
 
const int CALIB_ZERO_TANGENT_DIST = 0x00008
 
const int CirclesGridFinderParameters_ASYMMETRIC_GRID = 1
 
const int CirclesGridFinderParameters_SYMMETRIC_GRID = 0
 
const int COV_POLISHER = 3
 
const int CV_DLS = 3
 
const int CV_EPNP = 1
 
const int CV_ITERATIVE = 0
 
const int CV_P3P = 2
 
const int CvLevMarq_CALC_J = 2
 
const int CvLevMarq_CHECK_ERR = 3
 
const int CvLevMarq_DONE = 0
 
const int CvLevMarq_STARTED = 1
 
const int fisheye_CALIB_CHECK_COND = 1 << 2
 
const int fisheye_CALIB_FIX_FOCAL_LENGTH = 1 << 11
 
const int fisheye_CALIB_FIX_INTRINSIC = 1 << 8
 
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_PRINCIPAL_POINT = 1 << 9
 
const int fisheye_CALIB_FIX_SKEW = 1 << 3
 
const int fisheye_CALIB_RECOMPUTE_EXTRINSIC = 1 << 1
 
const int fisheye_CALIB_USE_INTRINSIC_GUESS = 1 << 0
 
const int fisheye_CALIB_ZERO_DISPARITY = 1 << 10
 
const int FM_7POINT = 1
 
const int FM_8POINT = 2
 
const int FM_LMEDS = 4
 
const int FM_RANSAC = 8
 
const int LMEDS = 4
 
const int LOCAL_OPTIM_GC = 3
 
const int LOCAL_OPTIM_INNER_AND_ITER_LO = 2
 
const int LOCAL_OPTIM_INNER_LO = 1
 
const int LOCAL_OPTIM_NULL = 0
 
const int LOCAL_OPTIM_SIGMA = 4
 
const int LSQ_POLISHER = 1
 
const int MAGSAC = 2
 
const int NEIGH_FLANN_KNN = 0
 
const int NEIGH_FLANN_RADIUS = 2
 
const int NEIGH_GRID = 1
 
const int NONE_POLISHER = 0
 
const int PROJ_SPHERICAL_EQRECT = 1
 
const int PROJ_SPHERICAL_ORTHO = 0
 
const int RANSAC = 8
 
const int RHO = 16
 
const int SAMPLING_NAPSAC = 2
 
const int SAMPLING_PROGRESSIVE_NAPSAC = 1
 
const int SAMPLING_PROSAC = 3
 
const int SAMPLING_UNIFORM = 0
 
const int SCORE_METHOD_LMEDS = 3
 
const int SCORE_METHOD_MAGSAC = 2
 
const int SCORE_METHOD_MSAC = 1
 
const int SCORE_METHOD_RANSAC = 0
 
const int SOLVEPNP_AP3P = 5
 
const int SOLVEPNP_DLS = 3
 
const int SOLVEPNP_EPNP = 1
 
const int SOLVEPNP_IPPE = 6
 
const int SOLVEPNP_IPPE_SQUARE = 7
 
const int SOLVEPNP_ITERATIVE = 0
 
const int SOLVEPNP_MAX_COUNT = 8 + 1
 
const int SOLVEPNP_P3P = 2
 
const int SOLVEPNP_SQPNP = 8
 
const int SOLVEPNP_UPNP = 4
 
const int USAC_ACCURATE = 36
 
const int USAC_DEFAULT = 32
 
const int USAC_FAST = 35
 
const int USAC_FM_8PTS = 34
 
const int USAC_MAGSAC = 38
 
const int USAC_PARALLEL = 33
 
const int USAC_PROSAC = 37
 
static double v0
 Estimates the sharpness of a detected chessboard.
 
static double double v1
 
static double double double v2
 
static int int int width
 
static int x
 
static int int y
 

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
objectPointsIn 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.
imagePointsIn 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.
imageSizeSize of the image used only to initialize the camera intrinsic matrix.
cameraMatrixInput/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.
distCoeffsInput/output vector of distortion coefficients \(\distcoeffs\).
rvecsOutput 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.
tvecsOutput vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsicsOutput 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.
stdDeviationsExtrinsicsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsIn 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.
imagePointsIn 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.
imageSizeSize of the image used only to initialize the camera intrinsic matrix.
cameraMatrixInput/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.
distCoeffsInput/output vector of distortion coefficients \(\distcoeffs\).
rvecsOutput 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.
tvecsOutput vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsicsOutput 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.
stdDeviationsExtrinsicsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsIn 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.
imagePointsIn 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.
imageSizeSize of the image used only to initialize the camera intrinsic matrix.
cameraMatrixInput/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.
distCoeffsInput/output vector of distortion coefficients \(\distcoeffs\).
rvecsOutput 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.
tvecsOutput vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsicsOutput 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.
stdDeviationsExtrinsicsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsIn 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.
imagePointsIn 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.
imageSizeSize of the image used only to initialize the camera intrinsic matrix.
cameraMatrixInput/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.
distCoeffsInput/output vector of distortion coefficients \(\distcoeffs\).
rvecsOutput 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.
tvecsOutput vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsicsOutput 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.
stdDeviationsExtrinsicsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsIn 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.
imagePointsIn 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.
imageSizeSize of the image used only to initialize the camera intrinsic matrix.
cameraMatrixInput/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.
distCoeffsInput/output vector of distortion coefficients \(\distcoeffs\).
rvecsOutput 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.
tvecsOutput vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsicsOutput 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.
stdDeviationsExtrinsicsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsIn 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.
imagePointsIn 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.
imageSizeSize of the image used only to initialize the camera intrinsic matrix.
cameraMatrixInput/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.
distCoeffsInput/output vector of distortion coefficients \(\distcoeffs\).
rvecsOutput 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.
tvecsOutput vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsicsOutput 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.
stdDeviationsExtrinsicsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsIn 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.
imagePointsIn 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.
imageSizeSize of the image used only to initialize the camera intrinsic matrix.
cameraMatrixInput/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.
distCoeffsInput/output vector of distortion coefficients \(\distcoeffs\).
rvecsOutput 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.
tvecsOutput vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsicsOutput 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.
stdDeviationsExtrinsicsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsIn 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.
imagePointsIn 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.
imageSizeSize of the image used only to initialize the camera intrinsic matrix.
cameraMatrixInput/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.
distCoeffsInput/output vector of distortion coefficients \(\distcoeffs\).
rvecsOutput 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.
tvecsOutput vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsicsOutput 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.
stdDeviationsExtrinsicsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsIn 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.
imagePointsIn 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.
imageSizeSize of the image used only to initialize the camera intrinsic matrix.
cameraMatrixInput/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.
distCoeffsInput/output vector of distortion coefficients \(\distcoeffs\).
rvecsOutput 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.
tvecsOutput vector of translation vectors estimated for each pattern view, see parameter describtion above.
stdDeviationsIntrinsicsOutput 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.
stdDeviationsExtrinsicsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsVector 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.
imagePointsVector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSizeSize of the image used only to initialize the intrinsic camera matrix.
iFixedPointThe 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.
cameraMatrixOutput 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffsOutput vector of distortion coefficients. See calibrateCamera for details.
rvecsOutput vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecsOutput vector of translation vectors estimated for each pattern view.
newObjPointsThe 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.
stdDeviationsIntrinsicsOutput vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsicsOutput vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPointsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsVector 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.
imagePointsVector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSizeSize of the image used only to initialize the intrinsic camera matrix.
iFixedPointThe 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.
cameraMatrixOutput 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffsOutput vector of distortion coefficients. See calibrateCamera for details.
rvecsOutput vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecsOutput vector of translation vectors estimated for each pattern view.
newObjPointsThe 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.
stdDeviationsIntrinsicsOutput vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsicsOutput vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPointsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsVector 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.
imagePointsVector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSizeSize of the image used only to initialize the intrinsic camera matrix.
iFixedPointThe 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.
cameraMatrixOutput 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffsOutput vector of distortion coefficients. See calibrateCamera for details.
rvecsOutput vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecsOutput vector of translation vectors estimated for each pattern view.
newObjPointsThe 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.
stdDeviationsIntrinsicsOutput vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsicsOutput vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPointsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsVector 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.
imagePointsVector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSizeSize of the image used only to initialize the intrinsic camera matrix.
iFixedPointThe 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.
cameraMatrixOutput 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffsOutput vector of distortion coefficients. See calibrateCamera for details.
rvecsOutput vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecsOutput vector of translation vectors estimated for each pattern view.
newObjPointsThe 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.
stdDeviationsIntrinsicsOutput vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsicsOutput vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPointsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsVector 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.
imagePointsVector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSizeSize of the image used only to initialize the intrinsic camera matrix.
iFixedPointThe 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.
cameraMatrixOutput 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffsOutput vector of distortion coefficients. See calibrateCamera for details.
rvecsOutput vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecsOutput vector of translation vectors estimated for each pattern view.
newObjPointsThe 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.
stdDeviationsIntrinsicsOutput vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsicsOutput vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPointsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsVector 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.
imagePointsVector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSizeSize of the image used only to initialize the intrinsic camera matrix.
iFixedPointThe 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.
cameraMatrixOutput 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffsOutput vector of distortion coefficients. See calibrateCamera for details.
rvecsOutput vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecsOutput vector of translation vectors estimated for each pattern view.
newObjPointsThe 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.
stdDeviationsIntrinsicsOutput vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsicsOutput vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPointsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsVector 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.
imagePointsVector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSizeSize of the image used only to initialize the intrinsic camera matrix.
iFixedPointThe 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.
cameraMatrixOutput 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffsOutput vector of distortion coefficients. See calibrateCamera for details.
rvecsOutput vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecsOutput vector of translation vectors estimated for each pattern view.
newObjPointsThe 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.
stdDeviationsIntrinsicsOutput vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsicsOutput vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPointsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsVector 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.
imagePointsVector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSizeSize of the image used only to initialize the intrinsic camera matrix.
iFixedPointThe 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.
cameraMatrixOutput 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffsOutput vector of distortion coefficients. See calibrateCamera for details.
rvecsOutput vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecsOutput vector of translation vectors estimated for each pattern view.
newObjPointsThe 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.
stdDeviationsIntrinsicsOutput vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsicsOutput vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPointsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
objectPointsVector 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.
imagePointsVector of vectors of the projections of calibration pattern points. See calibrateCamera for details.
imageSizeSize of the image used only to initialize the intrinsic camera matrix.
iFixedPointThe 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.
cameraMatrixOutput 3x3 floating-point camera matrix. See calibrateCamera for details.
distCoeffsOutput vector of distortion coefficients. See calibrateCamera for details.
rvecsOutput vector of rotation vectors estimated for each pattern view. See calibrateCamera for details.
tvecsOutput vector of translation vectors estimated for each pattern view.
newObjPointsThe 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.
stdDeviationsIntrinsicsOutput vector of standard deviations estimated for intrinsic parameters. See calibrateCamera for details.
stdDeviationsExtrinsicsOutput vector of standard deviations estimated for extrinsic parameters. See calibrateCamera for details.
stdDeviationsObjPointsOutput 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.
perViewErrorsOutput vector of the RMS re-projection error estimated for each pattern view.
flagsDifferent 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.
criteriaTermination 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
cameraMatrixInput camera intrinsic matrix that can be estimated by calibrateCamera or stereoCalibrate .
imageSizeInput image size in pixels.
apertureWidthPhysical width in mm of the sensor.
apertureHeightPhysical height in mm of the sensor.
fovxOutput field of view in degrees along the horizontal sensor axis.
fovyOutput field of view in degrees along the vertical sensor axis.
focalLengthFocal length of the lens in mm.
principalPointPrincipal 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
cameraMatrixInput camera intrinsic matrix that can be estimated by calibrateCamera or stereoCalibrate .
imageSizeInput image size in pixels.
apertureWidthPhysical width in mm of the sensor.
apertureHeightPhysical height in mm of the sensor.
fovxOutput field of view in degrees along the horizontal sensor axis.
fovyOutput field of view in degrees along the vertical sensor axis.
focalLengthFocal length of the lens in mm.
principalPointPrincipal 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
cameraMatrixInput camera intrinsic matrix that can be estimated by calibrateCamera or stereoCalibrate .
imageSizeInput image size in pixels.
apertureWidthPhysical width in mm of the sensor.
apertureHeightPhysical height in mm of the sensor.
fovxOutput field of view in degrees along the horizontal sensor axis.
fovyOutput field of view in degrees along the vertical sensor axis.
focalLengthFocal length of the lens in mm.
principalPointPrincipal 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
rvec1First rotation vector.
tvec1First translation vector.
rvec2Second rotation vector.
tvec2Second translation vector.
rvec3Output rotation vector of the superposition.
tvec3Output translation vector of the superposition.
dr3dr1Optional output derivative of rvec3 with regard to rvec1
dr3dt1Optional output derivative of rvec3 with regard to tvec1
dr3dr2Optional output derivative of rvec3 with regard to rvec2
dr3dt2Optional output derivative of rvec3 with regard to tvec2
dt3dr1Optional output derivative of tvec3 with regard to rvec1
dt3dt1Optional output derivative of tvec3 with regard to tvec1
dt3dr2Optional output derivative of tvec3 with regard to rvec2
dt3dt2Optional 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
rvec1First rotation vector.
tvec1First translation vector.
rvec2Second rotation vector.
tvec2Second translation vector.
rvec3Output rotation vector of the superposition.
tvec3Output translation vector of the superposition.
dr3dr1Optional output derivative of rvec3 with regard to rvec1
dr3dt1Optional output derivative of rvec3 with regard to tvec1
dr3dr2Optional output derivative of rvec3 with regard to rvec2
dr3dt2Optional output derivative of rvec3 with regard to tvec2
dt3dr1Optional output derivative of tvec3 with regard to rvec1
dt3dt1Optional output derivative of tvec3 with regard to tvec1
dt3dr2Optional output derivative of tvec3 with regard to rvec2
dt3dt2Optional 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
rvec1First rotation vector.
tvec1First translation vector.
rvec2Second rotation vector.
tvec2Second translation vector.
rvec3Output rotation vector of the superposition.
tvec3Output translation vector of the superposition.
dr3dr1Optional output derivative of rvec3 with regard to rvec1
dr3dt1Optional output derivative of rvec3 with regard to tvec1
dr3dr2Optional output derivative of rvec3 with regard to rvec2
dr3dt2Optional output derivative of rvec3 with regard to tvec2
dt3dr1Optional output derivative of tvec3 with regard to rvec1
dt3dt1Optional output derivative of tvec3 with regard to tvec1
dt3dr2Optional output derivative of tvec3 with regard to rvec2
dt3dt2Optional 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
rvec1First rotation vector.
tvec1First translation vector.
rvec2Second rotation vector.
tvec2Second translation vector.
rvec3Output rotation vector of the superposition.
tvec3Output translation vector of the superposition.
dr3dr1Optional output derivative of rvec3 with regard to rvec1
dr3dt1Optional output derivative of rvec3 with regard to tvec1
dr3dr2Optional output derivative of rvec3 with regard to rvec2
dr3dt2Optional output derivative of rvec3 with regard to tvec2
dt3dr1Optional output derivative of tvec3 with regard to rvec1
dt3dt1Optional output derivative of tvec3 with regard to tvec1
dt3dr2Optional output derivative of tvec3 with regard to rvec2
dt3dt2Optional 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
rvec1First rotation vector.
tvec1First translation vector.
rvec2Second rotation vector.
tvec2Second translation vector.
rvec3Output rotation vector of the superposition.
tvec3Output translation vector of the superposition.
dr3dr1Optional output derivative of rvec3 with regard to rvec1
dr3dt1Optional output derivative of rvec3 with regard to tvec1
dr3dr2Optional output derivative of rvec3 with regard to rvec2
dr3dt2Optional output derivative of rvec3 with regard to tvec2
dt3dr1Optional output derivative of tvec3 with regard to rvec1
dt3dt1Optional output derivative of tvec3 with regard to tvec1
dt3dr2Optional output derivative of tvec3 with regard to rvec2
dt3dt2Optional 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
rvec1First rotation vector.
tvec1First translation vector.
rvec2Second rotation vector.
tvec2Second translation vector.
rvec3Output rotation vector of the superposition.
tvec3Output translation vector of the superposition.
dr3dr1Optional output derivative of rvec3 with regard to rvec1
dr3dt1Optional output derivative of rvec3 with regard to tvec1
dr3dr2Optional output derivative of rvec3 with regard to rvec2
dr3dt2Optional output derivative of rvec3 with regard to tvec2
dt3dr1Optional output derivative of tvec3 with regard to rvec1
dt3dt1Optional output derivative of tvec3 with regard to tvec1
dt3dr2Optional output derivative of tvec3 with regard to rvec2
dt3dt2Optional 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
rvec1First rotation vector.
tvec1First translation vector.
rvec2Second rotation vector.
tvec2Second translation vector.
rvec3Output rotation vector of the superposition.
tvec3Output translation vector of the superposition.
dr3dr1Optional output derivative of rvec3 with regard to rvec1
dr3dt1Optional output derivative of rvec3 with regard to tvec1
dr3dr2Optional output derivative of rvec3 with regard to rvec2
dr3dt2Optional output derivative of rvec3 with regard to tvec2
dt3dr1Optional output derivative of tvec3 with regard to rvec1
dt3dt1Optional output derivative of tvec3 with regard to tvec1
dt3dr2Optional output derivative of tvec3 with regard to rvec2
dt3dt2Optional 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
rvec1First rotation vector.
tvec1First translation vector.
rvec2Second rotation vector.
tvec2Second translation vector.
rvec3Output rotation vector of the superposition.
tvec3Output translation vector of the superposition.
dr3dr1Optional output derivative of rvec3 with regard to rvec1
dr3dt1Optional output derivative of rvec3 with regard to tvec1
dr3dr2Optional output derivative of rvec3 with regard to rvec2
dr3dt2Optional output derivative of rvec3 with regard to tvec2
dt3dr1Optional output derivative of tvec3 with regard to rvec1
dt3dt1Optional output derivative of tvec3 with regard to tvec1
dt3dr2Optional output derivative of tvec3 with regard to rvec2
dt3dt2Optional 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
rvec1First rotation vector.
tvec1First translation vector.
rvec2Second rotation vector.
tvec2Second translation vector.
rvec3Output rotation vector of the superposition.
tvec3Output translation vector of the superposition.
dr3dr1Optional output derivative of rvec3 with regard to rvec1
dr3dt1Optional output derivative of rvec3 with regard to tvec1
dr3dr2Optional output derivative of rvec3 with regard to rvec2
dr3dt2Optional output derivative of rvec3 with regard to tvec2
dt3dr1Optional output derivative of tvec3 with regard to rvec1
dt3dt1Optional output derivative of tvec3 with regard to tvec1
dt3dr2Optional output derivative of tvec3 with regard to rvec2
dt3dt2Optional 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
pointsInput points. \(N \times 1\) or \(1 \times N\) matrix of type CV_32FC2 or vector<Point2f> .
whichImageIndex of the image (1 or 2) that contains the points .
FFundamental matrix that can be estimated using findFundamentalMat or stereoRectify .
linesOutput 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
srcInput vector of N-dimensional points.
dstOutput 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
srcInput vector of N-dimensional points.
dstOutput 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
F3x3 fundamental matrix.
points11xN array containing the first set of points.
points21xN array containing the second set of points.
newPoints1The optimized points1.
newPoints2The 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
EThe input essential matrix.
R1One possible rotation matrix.
R2Another possible rotation matrix.
tOne 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
HThe input homography matrix between two images.
KThe input camera intrinsic matrix.
rotationsArray of rotation matrices.
translationsArray of translation matrices.
normalsArray 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
projMatrix3x4 input projection matrix P.
cameraMatrixOutput 3x3 camera intrinsic matrix \(\cameramatrix{A}\).
rotMatrixOutput 3x3 external rotation matrix R.
transVectOutput 4x1 translation vector T.
rotMatrixXOptional 3x3 rotation matrix around x-axis.
rotMatrixYOptional 3x3 rotation matrix around y-axis.
rotMatrixZOptional 3x3 rotation matrix around z-axis.
eulerAnglesOptional 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
projMatrix3x4 input projection matrix P.
cameraMatrixOutput 3x3 camera intrinsic matrix \(\cameramatrix{A}\).
rotMatrixOutput 3x3 external rotation matrix R.
transVectOutput 4x1 translation vector T.
rotMatrixXOptional 3x3 rotation matrix around x-axis.
rotMatrixYOptional 3x3 rotation matrix around y-axis.
rotMatrixZOptional 3x3 rotation matrix around z-axis.
eulerAnglesOptional 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
projMatrix3x4 input projection matrix P.
cameraMatrixOutput 3x3 camera intrinsic matrix \(\cameramatrix{A}\).
rotMatrixOutput 3x3 external rotation matrix R.
transVectOutput 4x1 translation vector T.
rotMatrixXOptional 3x3 rotation matrix around x-axis.
rotMatrixYOptional 3x3 rotation matrix around y-axis.
rotMatrixZOptional 3x3 rotation matrix around z-axis.
eulerAnglesOptional 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
projMatrix3x4 input projection matrix P.
cameraMatrixOutput 3x3 camera intrinsic matrix \(\cameramatrix{A}\).
rotMatrixOutput 3x3 external rotation matrix R.
transVectOutput 4x1 translation vector T.
rotMatrixXOptional 3x3 rotation matrix around x-axis.
rotMatrixYOptional 3x3 rotation matrix around y-axis.
rotMatrixZOptional 3x3 rotation matrix around z-axis.
eulerAnglesOptional 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
projMatrix3x4 input projection matrix P.
cameraMatrixOutput 3x3 camera intrinsic matrix \(\cameramatrix{A}\).
rotMatrixOutput 3x3 external rotation matrix R.
transVectOutput 4x1 translation vector T.
rotMatrixXOptional 3x3 rotation matrix around x-axis.
rotMatrixYOptional 3x3 rotation matrix around y-axis.
rotMatrixZOptional 3x3 rotation matrix around z-axis.
eulerAnglesOptional 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
imageDestination image. It must be an 8-bit color image.
patternSizeNumber of inner corners per a chessboard row and column (patternSize = cv::Size(points_per_row,points_per_column)).
cornersArray of detected corners, the output of findChessboardCorners.
patternWasFoundParameter 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
imageDestination image. It must be an 8-bit color image.
patternSizeNumber of inner corners per a chessboard row and column (patternSize = cv::Size(points_per_row,points_per_column)).
cornersArray of detected corners, the output of findChessboardCorners.
patternWasFoundParameter 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
<
imageDestination image. It must be an 8-bit color image.
patternSizeNumber of inner corners per a chessboard row and column (patternSize = cv::Size(points_per_row,points_per_column)).
cornersArray of detected corners, the output of findChessboardCorners.
patternWasFound