OpenCV  3.4.19
Open Source Computer Vision
Static Public Member Functions | List of all members
cv::xfeatures2d::MSDDetector Class Reference

Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in [212]. More...

#include <opencv2/xfeatures2d.hpp>

Inheritance diagram for cv::xfeatures2d::MSDDetector:
cv::Feature2D cv::Algorithm

Static Public Member Functions

static Ptr< MSDDetectorcreate (int m_patch_radius=3, int m_search_area_radius=5, int m_nms_radius=5, int m_nms_scale_radius=0, float m_th_saliency=250.0f, int m_kNN=4, float m_scale_factor=1.25f, int m_n_scales=-1, bool m_compute_orientation=false)
 
- Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp > load (const String &filename, const String &objname=String())
 Loads algorithm from the file. More...
 
template<typename _Tp >
static Ptr< _Tp > loadFromString (const String &strModel, const String &objname=String())
 Loads algorithm from a String. More...
 
template<typename _Tp >
static Ptr< _Tp > read (const FileNode &fn)
 Reads algorithm from the file node. More...
 

Additional Inherited Members

- Public Member Functions inherited from cv::Feature2D
virtual ~Feature2D ()
 
virtual void compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray descriptors)
 Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant). More...
 
virtual void compute (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors)
 
virtual int defaultNorm () const
 
virtual int descriptorSize () const
 
virtual int descriptorType () const
 
virtual void detect (InputArray image, std::vector< KeyPoint > &keypoints, InputArray mask=noArray())
 Detects keypoints in an image (first variant) or image set (second variant). More...
 
virtual void detect (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray())
 
virtual void detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false)
 
virtual bool empty () const CV_OVERRIDE
 Return true if detector object is empty. More...
 
virtual String getDefaultName () const CV_OVERRIDE
 
void read (const String &fileName)
 
virtual void read (const FileNode &) CV_OVERRIDE
 Reads algorithm parameters from a file storage. More...
 
void write (const String &fileName) const
 
virtual void write (FileStorage &) const CV_OVERRIDE
 Stores algorithm parameters in a file storage. More...
 
void write (FileStorage &fs, const String &name) const
 
void write (const Ptr< FileStorage > &fs, const String &name) const
 
- Public Member Functions inherited from cv::Algorithm
 Algorithm ()
 
virtual ~Algorithm ()
 
virtual void clear ()
 Clears the algorithm state. More...
 
virtual void save (const String &filename) const
 
void write (FileStorage &fs, const String &name) const
 
void write (const Ptr< FileStorage > &fs, const String &name=String()) const
 
- Protected Member Functions inherited from cv::Algorithm
void writeFormat (FileStorage &fs) const
 

Detailed Description

Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in [212].

The algorithm implements a novel interest point detector stemming from the intuition that image patches which are highly dissimilar over a relatively large extent of their surroundings hold the property of being repeatable and distinctive. This concept of "contextual self-dissimilarity" reverses the key paradigm of recent successful techniques such as the Local Self-Similarity descriptor and the Non-Local Means filter, which build upon the presence of similar - rather than dissimilar - patches. Moreover, it extends to contextual information the local self-dissimilarity notion embedded in established detectors of corner-like interest points, thereby achieving enhanced repeatability, distinctiveness and localization accuracy.

Member Function Documentation

◆ create()

static Ptr<MSDDetector> cv::xfeatures2d::MSDDetector::create ( int  m_patch_radius = 3,
int  m_search_area_radius = 5,
int  m_nms_radius = 5,
int  m_nms_scale_radius = 0,
float  m_th_saliency = 250.0f,
int  m_kNN = 4,
float  m_scale_factor = 1.25f,
int  m_n_scales = -1,
bool  m_compute_orientation = false 
)
static
Python:
cv.xfeatures2d.MSDDetector.create([, m_patch_radius[, m_search_area_radius[, m_nms_radius[, m_nms_scale_radius[, m_th_saliency[, m_kNN[, m_scale_factor[, m_n_scales[, m_compute_orientation]]]]]]]]]) -> retval
cv.xfeatures2d.MSDDetector_create([, m_patch_radius[, m_search_area_radius[, m_nms_radius[, m_nms_scale_radius[, m_th_saliency[, m_kNN[, m_scale_factor[, m_n_scales[, m_compute_orientation]]]]]]]]]) -> retval

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