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| override string | getDefaultName () |
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| void | setUseScaleOrientation (bool use_scale_orientation) |
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| bool | getUseScaleOrientation () |
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| void | setScaleFactor (float scale_factor) |
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| float | getScaleFactor () |
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| void | detect (Mat image, MatOfKeyPoint keypoints, Mat mask) |
| | Detects keypoints in an image (first variant) or image set (second variant). More...
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| void | detect (Mat image, MatOfKeyPoint keypoints) |
| | Detects keypoints in an image (first variant) or image set (second variant). More...
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| void | detect (List< Mat > images, List< MatOfKeyPoint > keypoints, List< Mat > masks) |
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| void | detect (List< Mat > images, List< MatOfKeyPoint > keypoints) |
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| void | compute (Mat image, MatOfKeyPoint keypoints, Mat descriptors) |
| | Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant). More...
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| void | compute (List< Mat > images, List< MatOfKeyPoint > keypoints, List< Mat > descriptors) |
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| void | detectAndCompute (Mat image, Mat mask, MatOfKeyPoint keypoints, Mat descriptors, bool useProvidedKeypoints) |
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| void | detectAndCompute (Mat image, Mat mask, MatOfKeyPoint keypoints, Mat descriptors) |
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| int | descriptorSize () |
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| int | descriptorType () |
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| int | defaultNorm () |
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| void | write (string fileName) |
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| void | read (string fileName) |
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| override bool | empty () |
| | Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
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| IntPtr | getNativeObjAddr () |
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| virtual void | clear () |
| | Clears the algorithm state. More...
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| void | save (string filename) |
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| void | Dispose () |
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| void | ThrowIfDisposed () |
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Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in [Trzcinski13a] and [Trzcinski13b].
desc type of descriptor to use, BoostDesc::BINBOOST_256 is default (256 bit long dimension) Available types are: BoostDesc::BGM, BoostDesc::BGM_HARD, BoostDesc::BGM_BILINEAR, BoostDesc::LBGM, BoostDesc::BINBOOST_64, BoostDesc::BINBOOST_128, BoostDesc::BINBOOST_256 use_orientation sample patterns using keypoints orientation, enabled by default scale_factor adjust the sampling window of detected keypoints 6.25f is default and fits for KAZE, SURF detected keypoints window ratio 6.75f should be the scale for SIFT detected keypoints window ratio 5.00f should be the scale for AKAZE, MSD, AGAST, FAST, BRISK keypoints window ratio 0.75f should be the scale for ORB keypoints ratio 1.50f was the default in original implementation
- Note
- BGM is the base descriptor where each binary dimension is computed as the output of a single weak learner. BGM_HARD and BGM_BILINEAR refers to same BGM but use different type of gradient binning. In the BGM_HARD that use ASSIGN_HARD binning type the gradient is assigned to the nearest orientation bin. In the BGM_BILINEAR that use ASSIGN_BILINEAR binning type the gradient is assigned to the two neighbouring bins. In the BGM and all other modes that use ASSIGN_SOFT binning type the gradient is assigned to 8 nearest bins according to the cosine value between the gradient angle and the bin center. LBGM (alias FP-Boost) is the floating point extension where each dimension is computed as a linear combination of the weak learner responses. BINBOOST and subvariants are the binary extensions of LBGM where each bit is computed as a thresholded linear combination of a set of weak learners. BoostDesc header files (boostdesc_*.i) was exported from original binaries with export-boostdesc.py script from samples subfolder.
Public Member Functions inherited from OpenCVForUnity.Features2dModule.Feature2D