OpenCV  4.10.0-dev
Open Source Computer Vision
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Classes | Typedefs | Functions
cv::xfeatures2d Namespace Reference

Classes

class  AffineFeature2D
 Class implementing affine adaptation for key points. More...
 
class  BEBLID
 Class implementing BEBLID (Boosted Efficient Binary Local Image Descriptor), described in [256] . More...
 
class  BoostDesc
 Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in [261] and [262]. More...
 
class  BriefDescriptorExtractor
 Class for computing BRIEF descriptors described in [47] . More...
 
class  DAISY
 Class implementing DAISY descriptor, described in [270]. More...
 
class  Elliptic_KeyPoint
 Elliptic region around an interest point. More...
 
class  FREAK
 Class implementing the FREAK (Fast Retina Keypoint) keypoint descriptor, described in [8] . More...
 
class  HarrisLaplaceFeatureDetector
 Class implementing the Harris-Laplace feature detector as described in [193]. More...
 
class  LATCH
 
class  LUCID
 Class implementing the locally uniform comparison image descriptor, described in [321]. More...
 
class  MSDDetector
 Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in [271]. More...
 
class  PCTSignatures
 Class implementing PCT (position-color-texture) signature extraction as described in [152]. 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. More...
 
class  PCTSignaturesSQFD
 Class implementing Signature Quadratic Form Distance (SQFD). More...
 
class  StarDetector
 The class implements the keypoint detector introduced by [2], synonym of StarDetector. : More...
 
class  SURF
 Class for extracting Speeded Up Robust Features from an image [20] . More...
 
class  TBMR
 Class implementing the Tree Based Morse Regions (TBMR) as described in [307] extended with scaled extraction ability. More...
 
class  TEBLID
 Class implementing TEBLID (Triplet-based Efficient Binary Local Image Descriptor), described in [257]. More...
 
class  VGG
 Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in [246]. More...
 

Typedefs

typedef SURF SurfDescriptorExtractor
 
typedef SURF SurfFeatureDetector
 

Functions

void FASTForPointSet (InputArray image, std::vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression=true, cv::FastFeatureDetector::DetectorType type=FastFeatureDetector::TYPE_9_16)
 Estimates cornerness for prespecified KeyPoints using the FAST algorithm.
 
void matchGMS (const Size &size1, const Size &size2, const std::vector< KeyPoint > &keypoints1, const std::vector< KeyPoint > &keypoints2, const std::vector< DMatch > &matches1to2, std::vector< DMatch > &matchesGMS, const bool withRotation=false, const bool withScale=false, const double thresholdFactor=6.0)
 GMS (Grid-based Motion Statistics) feature matching strategy described in [26] .
 
void matchLOGOS (const std::vector< KeyPoint > &keypoints1, const std::vector< KeyPoint > &keypoints2, const std::vector< int > &nn1, const std::vector< int > &nn2, std::vector< DMatch > &matches1to2)
 LOGOS (Local geometric support for high-outlier spatial verification) feature matching strategy described in [175] .