[−][src]Module opencv::xfeatures2d
Extra 2D Features Framework
Experimental 2D Features Algorithms
This section describes experimental algorithms for 2d feature detection.
Non-free 2D Features Algorithms
This section describes two popular algorithms for 2d feature detection, SIFT and SURF, that are known to be patented. You need to set the OPENCV_ENABLE_NONFREE option in cmake to use those. Use them at your own risk.
Experimental 2D Features Matching Algorithm
This section describes the GMS (Grid-based Motion Statistics) matching strategy.
Structs
BriefDescriptorExtractor | Class for computing BRIEF descriptors described in calon2010 . |
Elliptic_KeyPoint | Elliptic region around an interest point. |
FREAK | Class implementing the FREAK (Fast Retina Keypoint) keypoint descriptor, described in AOV12 . |
HarrisLaplaceFeatureDetector | Class implementing the Harris-Laplace feature detector as described in Mikolajczyk2004. |
LATCH | latch Class for computing the LATCH descriptor. If you find this code useful, please add a reference to the following paper in your work: Gil Levi and Tal Hassner, "LATCH: Learned Arrangements of Three Patch Codes", arXiv preprint arXiv:1501.03719, 15 Jan. 2015 |
LUCID | Class implementing the locally uniform comparison image descriptor, described in LUCID |
MSDDetector | Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in Tombari14. |
SIFT | Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe Lowe04 . |
StarDetector | The class implements the keypoint detector introduced by Agrawal08, synonym of StarDetector. : |
Constants
DAISY_NRM_FULL | |
DAISY_NRM_NONE | |
DAISY_NRM_PARTIAL | |
DAISY_NRM_SIFT | |
FREAK_NB_ORIENPAIRS | |
FREAK_NB_PAIRS | |
FREAK_NB_SCALES | |
PCTSignatures_GAUSSIAN |
block formula |
PCTSignatures_HEURISTIC |
block formula |
PCTSignatures_L1 | |
PCTSignatures_L2 | |
PCTSignatures_L2SQUARED | |
PCTSignatures_L5 | |
PCTSignatures_L0_5 | |
PCTSignatures_L0_25 | |
PCTSignatures_L_INFINITY | |
PCTSignatures_MINUS |
block formula |
PCTSignatures_NORMAL | Generate points with normal (gaussian) distribution. |
PCTSignatures_REGULAR | Generate points in a regular grid. |
PCTSignatures_UNIFORM | Generate numbers uniformly. |
Traits
AffineFeature2D | Class implementing affine adaptation for key points. |
BoostDesc | Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in Trzcinski13a and Trzcinski13b. |
DAISY | Class implementing DAISY descriptor, described in Tola10 |
PCTSignatures | Class implementing PCT (position-color-texture) signature extraction as described in KrulisLS16. The algorithm is divided to a feature sampler and a clusterizer. Feature sampler produces samples at given set of coordinates. Clusterizer then produces clusters of these samples using k-means algorithm. Resulting set of clusters is the signature of the input image. |
PCTSignaturesSQFD | Class implementing Signature Quadratic Form Distance (SQFD). @see Christian Beecks, Merih Seran Uysal, Thomas Seidl. Signature quadratic form distance. In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445. ACM, 2010. BeecksUS10 |
SURF | Class for extracting Speeded Up Robust Features from an image Bay06 . |
VGG | Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in Simonyan14. |
Functions
fast_for_point_set | Estimates cornerness for prespecified KeyPoints using the FAST algorithm |
match_gms | GMS (Grid-based Motion Statistics) feature matching strategy by Bian2017gms . |