Experimental 2D Features Algorithms

Classes
class	cv::xfeatures2d::BoostDesc
	Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in [148] and [149]. More...
class	cv::xfeatures2d::BriefDescriptorExtractor
	Class for computing BRIEF descriptors described in [25] . More...
class	cv::xfeatures2d::DAISY
	Class implementing DAISY descriptor, described in [153]. More...
class	cv::xfeatures2d::FREAK
	Class implementing the FREAK (Fast Retina Keypoint) keypoint descriptor, described in [4] . More...
class	cv::xfeatures2d::LATCH
class	cv::xfeatures2d::LUCID
	Class implementing the locally uniform comparison image descriptor, described in [186]. More...
class	cv::xfeatures2d::MSDDetector
	Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in [154]. More...
class	cv::xfeatures2d::PCTSignatures
	Class implementing PCT (position-color-texture) signature extraction as described in [86]. 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	cv::xfeatures2d::PCTSignaturesSQFD
	Class implementing Signature Quadratic Form Distance (SQFD). More...
class	cv::xfeatures2d::StarDetector
	The class implements the keypoint detector introduced by [2], synonym of StarDetector. : More...
class	cv::xfeatures2d::VGG
	Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in [141]. More...

Detailed Description

This section describes experimental algorithms for 2d feature detection.