OpenCV453
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Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in [Tombari14]. [詳解]
#include <xfeatures2d.hpp>
cv::Feature2Dを継承しています。
静的公開メンバ関数 | |
static Ptr< 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) |
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template<typename _Tp > | |
static Ptr< _Tp > | read (const FileNode &fn) |
Reads algorithm from the file node [詳解] | |
template<typename _Tp > | |
static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
Loads algorithm from the file [詳解] | |
template<typename _Tp > | |
static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
Loads algorithm from a String [詳解] | |
その他の継承メンバ | |
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virtual CV_WRAP void | detect (InputArray image, CV_OUT std::vector< KeyPoint > &keypoints, InputArray mask=noArray()) |
Detects keypoints in an image (first variant) or image set (second variant). [詳解] | |
virtual CV_WRAP void | detect (InputArrayOfArrays images, CV_OUT std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray()) |
virtual CV_WRAP void | compute (InputArray image, CV_OUT CV_IN_OUT 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). [詳解] | |
virtual CV_WRAP void | compute (InputArrayOfArrays images, CV_OUT CV_IN_OUT std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors) |
virtual CV_WRAP void | detectAndCompute (InputArray image, InputArray mask, CV_OUT std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false) |
virtual CV_WRAP int | descriptorSize () const |
virtual CV_WRAP int | descriptorType () const |
virtual CV_WRAP int | defaultNorm () const |
CV_WRAP void | write (const String &fileName) const |
CV_WRAP void | read (const String &fileName) |
virtual void | write (FileStorage &) const CV_OVERRIDE |
Stores algorithm parameters in a file storage [詳解] | |
virtual CV_WRAP void | read (const FileNode &) CV_OVERRIDE |
Reads algorithm parameters from a file storage [詳解] | |
virtual CV_WRAP bool | empty () const CV_OVERRIDE |
Return true if detector object is empty [詳解] | |
virtual CV_WRAP String | getDefaultName () const CV_OVERRIDE |
CV_WRAP void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
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virtual CV_WRAP void | clear () |
Clears the algorithm state [詳解] | |
CV_WRAP void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
simplified API for language bindings これはオーバーロードされたメンバ関数です。利便性のために用意されています。元の関数との違いは引き数のみです。 | |
virtual CV_WRAP void | save (const String &filename) const |
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void | writeFormat (FileStorage &fs) const |
Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in [Tombari14].
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.