Module 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

AffineFeature2D

Class implementing affine adaptation for key points.

BEBLID

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.

BriefDescriptorExtractor

Class for computing BRIEF descriptors described in calon2010 .

DAISY

Class implementing DAISY descriptor, described in Tola10

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.

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_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. :

TBMR

Class implementing the Tree Based Morse Regions (TBMR) as described in Najman2014 extended with scaled extraction ability.

TEBLID

Class implementing TEBLID (Triplet-based Efficient Binary Local Image Descriptor), described in Suarez2021TEBLID.

VGG

Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using “Descriptor Learning Using Convex Optimisation” (DLCO) aparatus described in Simonyan14.

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

TEBLID_TeblidSize

Descriptor number of bits, each bit is a box average difference. The user can choose between 256 or 512 bits.

Constants

BEBLID_SIZE_256_BITS

BEBLID_SIZE_512_BITS

BoostDesc_BGM

BoostDesc_BGM_BILINEAR

BoostDesc_BGM_HARD

BoostDesc_BINBOOST_64

BoostDesc_BINBOOST_128

BoostDesc_BINBOOST_256

BoostDesc_LBGM

DAISY_NRM_FULL

DAISY_NRM_NONE

DAISY_NRM_PARTIAL

DAISY_NRM_SIFT

PCTSignatures_GAUSSIAN

block formula

PCTSignatures_HEURISTIC

block formula

PCTSignatures_L0_5

PCTSignatures_L0_25

PCTSignatures_L1

PCTSignatures_L2

PCTSignatures_L5

PCTSignatures_L2SQUARED

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.

SURF_CUDA_ANGLE_ROW

SURF_CUDA_HESSIAN_ROW

SURF_CUDA_LAPLACIAN_ROW

SURF_CUDA_OCTAVE_ROW

SURF_CUDA_ROWS_COUNT

SURF_CUDA_SIZE_ROW

SURF_CUDA_X_ROW

SURF_CUDA_Y_ROW

TEBLID_SIZE_256_BITS

TEBLID_SIZE_512_BITS

VGG_VGG_48

VGG_VGG_64

VGG_VGG_80

VGG_VGG_120

Traits

AffineFeature2DTrait

Mutable methods for crate::xfeatures2d::AffineFeature2D

AffineFeature2DTraitConst

Constant methods for crate::xfeatures2d::AffineFeature2D

BEBLIDTrait

Mutable methods for crate::xfeatures2d::BEBLID

BEBLIDTraitConst

Constant methods for crate::xfeatures2d::BEBLID

BoostDescTrait

Mutable methods for crate::xfeatures2d::BoostDesc

BoostDescTraitConst

Constant methods for crate::xfeatures2d::BoostDesc

BriefDescriptorExtractorTrait

Mutable methods for crate::xfeatures2d::BriefDescriptorExtractor

BriefDescriptorExtractorTraitConst

Constant methods for crate::xfeatures2d::BriefDescriptorExtractor

DAISYTrait

Mutable methods for crate::xfeatures2d::DAISY

DAISYTraitConst

Constant methods for crate::xfeatures2d::DAISY

Elliptic_KeyPointTrait

Mutable methods for crate::xfeatures2d::Elliptic_KeyPoint

Elliptic_KeyPointTraitConst

Constant methods for crate::xfeatures2d::Elliptic_KeyPoint

FREAKTrait

Mutable methods for crate::xfeatures2d::FREAK

FREAKTraitConst

Constant methods for crate::xfeatures2d::FREAK

HarrisLaplaceFeatureDetectorTrait

Mutable methods for crate::xfeatures2d::HarrisLaplaceFeatureDetector

HarrisLaplaceFeatureDetectorTraitConst

Constant methods for crate::xfeatures2d::HarrisLaplaceFeatureDetector

LATCHTrait

Mutable methods for crate::xfeatures2d::LATCH

LATCHTraitConst

Constant methods for crate::xfeatures2d::LATCH

LUCIDTrait

Mutable methods for crate::xfeatures2d::LUCID

LUCIDTraitConst

Constant methods for crate::xfeatures2d::LUCID

MSDDetectorTrait

Mutable methods for crate::xfeatures2d::MSDDetector

MSDDetectorTraitConst

Constant methods for crate::xfeatures2d::MSDDetector

PCTSignaturesSQFDTrait

Mutable methods for crate::xfeatures2d::PCTSignaturesSQFD

PCTSignaturesSQFDTraitConst

Constant methods for crate::xfeatures2d::PCTSignaturesSQFD

PCTSignaturesTrait

Mutable methods for crate::xfeatures2d::PCTSignatures

PCTSignaturesTraitConst

Constant methods for crate::xfeatures2d::PCTSignatures

SURFTrait

Mutable methods for crate::xfeatures2d::SURF

SURFTraitConst

Constant methods for crate::xfeatures2d::SURF

SURF_CUDATrait

Mutable methods for crate::xfeatures2d::SURF_CUDA

SURF_CUDATraitConst

Constant methods for crate::xfeatures2d::SURF_CUDA

StarDetectorTrait

Mutable methods for crate::xfeatures2d::StarDetector

StarDetectorTraitConst

Constant methods for crate::xfeatures2d::StarDetector

TBMRTrait

Mutable methods for crate::xfeatures2d::TBMR

TBMRTraitConst

Constant methods for crate::xfeatures2d::TBMR

TEBLIDTrait

Mutable methods for crate::xfeatures2d::TEBLID

TEBLIDTraitConst

Constant methods for crate::xfeatures2d::TEBLID

VGGTrait

Mutable methods for crate::xfeatures2d::VGG

VGGTraitConst

Constant methods for crate::xfeatures2d::VGG

Functions

fast_for_point_set

Estimates cornerness for prespecified KeyPoints using the FAST algorithm

fast_for_point_set_def

Estimates cornerness for prespecified KeyPoints using the FAST algorithm

match_gms

GMS (Grid-based Motion Statistics) feature matching strategy described in Bian2017gms .

match_gms_def

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 Aliases

SurfDescriptorExtractor

SurfFeatureDetector