cv::KeyPoint Class Reference

#include <features2d.hpp>

List of all members.

Public Member Functions

CV_WRAP 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
 KeyPoint (Point2f _pt, float _size, float _angle=-1, float _response=0, int _octave=0, int _class_id=-1)
 the full constructor
CV_WRAP KeyPoint ()
 the default constructor

Static Public Member Functions

static void convert (const std::vector< Point2f > &points2f, CV_OUT std::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
static void convert (const std::vector< KeyPoint > &keypoints, CV_OUT std::vector< Point2f > &points2f, const std::vector< int > &keypointIndexes=std::vector< int >())
 converts vector of keypoints to vector of points
static float overlap (const KeyPoint &kp1, const KeyPoint &kp2)

Public Attributes

CV_PROP_RW float angle
 computed orientation of the keypoint (-1 if not applicable)
CV_PROP_RW int class_id
 object class (if the keypoints need to be clustered by an object they belong to)
CV_PROP_RW int octave
 octave (pyramid layer) from which the keypoint has been extracted
CV_PROP_RW Point2f pt
 coordinates of the keypoints
CV_PROP_RW float response
 the response by which the most strong keypoints have been selected. Can be used for the further sorting or subsampling
CV_PROP_RW float size
 diameter of the meaningfull keypoint neighborhood

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_WRAP 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_WRAP 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 std::vector< Point2f > &  points2f,
CV_OUT std::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

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

converts vector of keypoints to vector of points

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

CV_PROP_RW float cv::KeyPoint::angle

computed orientation of the keypoint (-1 if not applicable)

CV_PROP_RW int cv::KeyPoint::class_id

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

CV_PROP_RW int cv::KeyPoint::octave

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

coordinates of the keypoints

CV_PROP_RW float cv::KeyPoint::response

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

CV_PROP_RW float cv::KeyPoint::size

diameter of the meaningfull keypoint neighborhood


The documentation for this class was generated from the following file:
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Generated on Thu Dec 23 11:40:55 2010 for opencv by  doxygen 1.6.3