Class for extracting Speeded Up Robust Features from an image [Bay06] . [詳解]

#include <nonfree.hpp>

cv::Feature2Dを継承しています。

公開メンバ関数
virtual CV_WRAP void	setHessianThreshold (double hessianThreshold)=0

virtual CV_WRAP double	getHessianThreshold () const =0

virtual CV_WRAP void	setNOctaves (int nOctaves)=0

virtual CV_WRAP int	getNOctaves () const =0

virtual CV_WRAP void	setNOctaveLayers (int nOctaveLayers)=0

virtual CV_WRAP int	getNOctaveLayers () const =0

virtual CV_WRAP void	setExtended (bool extended)=0

virtual CV_WRAP bool	getExtended () const =0

virtual CV_WRAP void	setUpright (bool upright)=0

virtual CV_WRAP bool	getUpright () const =0

基底クラス cv::Feature2D に属する継承公開メンバ関数
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

基底クラス cv::Algorithm に属する継承公開メンバ関数
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

静的公開メンバ関数
static CV_WRAP Ptr< SURF >	create (double hessianThreshold=100, int nOctaves=4, int nOctaveLayers=3, bool extended=false, bool upright=false)

基底クラス cv::Algorithm に属する継承静的公開メンバ関数
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
基底クラス cv::Algorithm に属する継承限定公開メンバ関数
void	writeFormat (FileStorage &fs) const

詳解

Class for extracting Speeded Up Robust Features from an image [Bay06] .

The algorithm parameters:

member int extended
- 0 means that the basic descriptors (64 elements each) shall be computed
- 1 means that the extended descriptors (128 elements each) shall be computed
member int upright
- 0 means that detector computes orientation of each feature.
- 1 means that the orientation is not computed (which is much, much faster). For example, if you match images from a stereo pair, or do image stitching, the matched features likely have very similar angles, and you can speed up feature extraction by setting upright=1.
member double hessianThreshold Threshold for the keypoint detector. Only features, whose hessian is larger than hessianThreshold are retained by the detector. Therefore, the larger the value, the less keypoints you will get. A good default value could be from 300 to 500, depending from the image contrast.
member int nOctaves The number of a gaussian pyramid octaves that the detector uses. It is set to 4 by default. If you want to get very large features, use the larger value. If you want just small features, decrease it.
member int nOctaveLayers The number of images within each octave of a gaussian pyramid. It is set to 2 by default.
覚え書き
- An example using the SURF feature detector can be found at opencv_source_code/samples/cpp/generic_descriptor_match.cpp
  - Another example using the SURF feature detector, extractor and matcher can be found at opencv_source_code/samples/cpp/matcher_simple.cpp

関数詳解

◆ create()

static CV_WRAP Ptr< SURF > cv::xfeatures2d::SURF::create	(	double	hessianThreshold = `100`,
		int	nOctaves = `4`,
		int	nOctaveLayers = `3`,
		bool	extended = `false`,
		bool	upright = `false`
	)

static

引数

hessianThreshold	Threshold for hessian keypoint detector used in SURF.
nOctaves	Number of pyramid octaves the keypoint detector will use.
nOctaveLayers	Number of octave layers within each octave.
extended	Extended descriptor flag (true - use extended 128-element descriptors; false - use 64-element descriptors).
upright	Up-right or rotated features flag (true - do not compute orientation of features; false - compute orientation).

このクラス詳解は次のファイルから抽出されました:

nonfree.hpp

公開メンバ関数

静的公開メンバ関数

その他の継承メンバ

詳解

関数詳解

◆ create()