cv::KeyPoint Class Reference

#include <features2d.hpp>

Public Member Functions
	KeyPoint ()
	the default constructor More...
	KeyPoint (Point2f _pt, float _size, float _angle=-1, float _response=0, int _octave=0, int _class_id=-1)
	the full constructor More...
	KeyPoint (float x, float y, float _size, float _angle=-1, float _response=0, int _octave=0, int _class_id=-1)
	another form of the full constructor More...
size_t	hash () const

Static Public Member Functions
static void	convert (const vector< KeyPoint > &keypoints, CV_OUT vector< Point2f > &points2f, const vector< int > &keypointIndexes=vector< int >())
	converts vector of keypoints to vector of points More...
static void	convert (const vector< Point2f > &points2f, CV_OUT vector< KeyPoint > &keypoints, float size=1, float response=1, int octave=0, int class_id=-1)
	converts vector of points to the vector of keypoints, where each keypoint is assigned the same size and the same orientation More...
static float	overlap (const KeyPoint &kp1, const KeyPoint &kp2)

Public Attributes
Point2f	pt
	coordinates of the keypoints More...
float	size
	diameter of the meaningful keypoint neighborhood More...
float	angle
float	response
	the response by which the most strong keypoints have been selected. Can be used for the further sorting or subsampling More...
int	octave
	octave (pyramid layer) from which the keypoint has been extracted More...
int	class_id
	object class (if the keypoints need to be clustered by an object they belong to) More...

Detailed Description

The Keypoint Class

The class instance stores a keypoint, i.e. a point feature found by one of many available keypoint detectors, such as Harris corner detector, cv::FAST, cv::StarDetector, cv::SURF, cv::SIFT, cv::LDetector etc.

The keypoint is characterized by the 2D position, scale (proportional to the diameter of the neighborhood that needs to be taken into account), orientation and some other parameters. The keypoint neighborhood is then analyzed by another algorithm that builds a descriptor (usually represented as a feature vector). The keypoints representing the same object in different images can then be matched using cv::KDTree or another method.

Constructor & Destructor Documentation

cv::KeyPoint::KeyPoint ( )

inline

the default constructor

cv::KeyPoint::KeyPoint ( Point2f  _pt, float  _size, float  _angle = -1, float  _response = 0, int  _octave = 0, int  _class_id = -1  )

inline

the full constructor

cv::KeyPoint::KeyPoint ( float  x, float  y, float  _size, float  _angle = -1, float  _response = 0, int  _octave = 0, int  _class_id = -1  )

inline

another form of the full constructor

Member Function Documentation

static void cv::KeyPoint::convert ( const vector< KeyPoint > &  keypoints, CV_OUT vector< Point2f > &  points2f, const vector< int > &  keypointIndexes = vector< int >()  )

static

converts vector of keypoints to vector of points

static void cv::KeyPoint::convert ( const vector< Point2f > &  points2f, CV_OUT vector< KeyPoint > &  keypoints, float  size = 1, float  response = 1, int  octave = 0, int  class_id = -1  )

static

converts vector of points to the vector of keypoints, where each keypoint is assigned the same size and the same orientation

size_t cv::KeyPoint::hash

(

)

const

static float cv::KeyPoint::overlap ( const KeyPoint &  kp1, const KeyPoint &  kp2  )

static

computes overlap for pair of keypoints; overlap is a ratio between area of keypoint regions intersection and area of keypoint regions union (now keypoint region is circle)

Member Data Documentation

float cv::KeyPoint::angle

computed orientation of the keypoint (-1 if not applicable); it's in [0,360) degrees and measured relative to image coordinate system, ie in clockwise.

int cv::KeyPoint::class_id

object class (if the keypoints need to be clustered by an object they belong to)

int cv::KeyPoint::octave

octave (pyramid layer) from which the keypoint has been extracted

Point2f cv::KeyPoint::pt

coordinates of the keypoints

float cv::KeyPoint::response

the response by which the most strong keypoints have been selected. Can be used for the further sorting or subsampling

float cv::KeyPoint::size

diameter of the meaningful keypoint neighborhood

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The documentation for this class was generated from the following file:

• features2d/include/opencv2/features2d/features2d.hpp