cv::SIFT クラス

Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe [Lowe04] . [詳解]

#include <features2d.hpp>

cv::Feature2Dを継承しています。

公開メンバ関数
virtual CV_WRAP String	getDefaultName () const CV_OVERRIDE
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]
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< SIFT >	create (int nfeatures=0, int nOctaveLayers=3, double contrastThreshold=0.04, double edgeThreshold=10, double sigma=1.6)
static CV_WRAP Ptr< SIFT >	create (int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType)
	Create SIFT with specified descriptorType. [詳解]
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 keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe [Lowe04] .

関数詳解

create() [1/2]

static CV_WRAP Ptr< SIFT > cv::SIFT::create ( int  nfeatures, int  nOctaveLayers, double  contrastThreshold, double  edgeThreshold, double  sigma, int  descriptorType  )

static

Create SIFT with specified descriptorType.

引数

nfeatures	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers	The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold	The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

覚え書き

The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

引数

edgeThreshold	The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma	The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
descriptorType	The type of descriptors. Only CV_32F and CV_8U are supported.

create() [2/2]

static CV_WRAP Ptr< SIFT > cv::SIFT::create ( int  nfeatures = 0, int  nOctaveLayers = 3, double  contrastThreshold = 0.04, double  edgeThreshold = 10, double  sigma = 1.6  )

static

引数

nfeatures	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers	The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold	The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.

覚え書き

The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.

引数

edgeThreshold	The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma	The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.

getDefaultName()

virtual CV_WRAP String cv::SIFT::getDefaultName ( ) const

virtual

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

cv::Feature2Dを再実装しています。

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このクラス詳解は次のファイルから抽出されました:

• features2d.hpp