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 following matching strategies:

• GMS: Grid-based Motion Statistics, Bian2017gms
• LOGOS: Local geometric support for high-outlier spatial verification, Lowry2018LOGOSLG

Modules

prelude

Structs

BEBLID	Class implementing BEBLID (Boosted Efficient Binary Local Image Descriptor), described in Suarez2020BEBLID .
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.
SURF_CUDA	Class used for extracting Speeded Up Robust Features (SURF) from an image. :
StarDetector	The class implements the keypoint detector introduced by Agrawal08, synonym of StarDetector. :

Enums

BEBLID_BeblidSize	Descriptor number of bits, each bit is a boosting weak-learner. The user can choose between 512 or 256 bits.
DAISY_NormalizationType
PCTSignatures_DistanceFunction	Lp distance function selector.
PCTSignatures_PointDistribution	Point distributions supported by random point generator.
PCTSignatures_SimilarityFunction	Similarity function selector.
SURF_CUDA_KeypointLayout

Constants

BoostDesc_BGM
BoostDesc_BGM_BILINEAR
BoostDesc_BGM_HARD
BoostDesc_BINBOOST_64
BoostDesc_BINBOOST_128
BoostDesc_BINBOOST_256
BoostDesc_LBGM
VGG_VGG_48
VGG_VGG_64
VGG_VGG_80
VGG_VGG_120

Traits

AffineFeature2D	Class implementing affine adaptation for key points.
BEBLIDTrait	Class implementing BEBLID (Boosted Efficient Binary Local Image Descriptor), described in Suarez2020BEBLID .
BoostDesc	Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in Trzcinski13a and Trzcinski13b.
BriefDescriptorExtractorTrait	Class for computing BRIEF descriptors described in calon2010 .
DAISY	Class implementing DAISY descriptor, described in Tola10
Elliptic_KeyPointTrait	Elliptic region around an interest point.
FREAKTrait	Class implementing the FREAK (Fast Retina Keypoint) keypoint descriptor, described in AOV12 .
HarrisLaplaceFeatureDetectorTrait	Class implementing the Harris-Laplace feature detector as described in Mikolajczyk2004.
LATCHTrait	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
LUCIDTrait	Class implementing the locally uniform comparison image descriptor, described in LUCID
MSDDetectorTrait	Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in Tombari14.
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).
SURF	Class for extracting Speeded Up Robust Features from an image Bay06 .
SURF_CUDATrait	Class used for extracting Speeded Up Robust Features (SURF) from an image. :
StarDetectorTrait	The class implements the keypoint detector introduced by Agrawal08, synonym of StarDetector. :
TBMR	Class implementing the Tree Based Morse Regions (TBMR) as described in Najman2014 extended with scaled extraction ability.
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 described in Bian2017gms .
match_logos	LOGOS (Local geometric support for high-outlier spatial verification) feature matching strategy described in Lowry2018LOGOSLG .

Type Definitions

SurfDescriptorExtractor
SurfFeatureDetector