cv::BackgroundSubtractorKNN クラス

K-nearest neighbours - based Background/Foreground Segmentation Algorithm. [詳解]

#include <background_segm.hpp>

cv::BackgroundSubtractorを継承しています。

公開メンバ関数
virtual CV_WRAP int	getHistory () const =0
	Returns the number of last frames that affect the background model
virtual CV_WRAP void	setHistory (int history)=0
	Sets the number of last frames that affect the background model
virtual CV_WRAP int	getNSamples () const =0
	Returns the number of data samples in the background model
virtual CV_WRAP void	setNSamples (int _nN)=0
	Sets the number of data samples in the background model. [詳解]
virtual CV_WRAP double	getDist2Threshold () const =0
	Returns the threshold on the squared distance between the pixel and the sample [詳解]
virtual CV_WRAP void	setDist2Threshold (double _dist2Threshold)=0
	Sets the threshold on the squared distance
virtual CV_WRAP int	getkNNSamples () const =0
	Returns the number of neighbours, the k in the kNN. [詳解]
virtual CV_WRAP void	setkNNSamples (int _nkNN)=0
	Sets the k in the kNN. How many nearest neighbours need to match.
virtual CV_WRAP bool	getDetectShadows () const =0
	Returns the shadow detection flag [詳解]
virtual CV_WRAP void	setDetectShadows (bool detectShadows)=0
	Enables or disables shadow detection
virtual CV_WRAP int	getShadowValue () const =0
	Returns the shadow value [詳解]
virtual CV_WRAP void	setShadowValue (int value)=0
	Sets the shadow value
virtual CV_WRAP double	getShadowThreshold () const =0
	Returns the shadow threshold [詳解]
virtual CV_WRAP void	setShadowThreshold (double threshold)=0
	Sets the shadow threshold
基底クラス cv::BackgroundSubtractor に属する継承公開メンバ関数
virtual CV_WRAP void	apply (InputArray image, OutputArray fgmask, double learningRate=-1)=0
	Computes a foreground mask. [詳解]
virtual CV_WRAP void	getBackgroundImage (OutputArray backgroundImage) const =0
	Computes a background image. [詳解]
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]
virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage [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	read (const FileNode &fn)
	Reads algorithm parameters from a file storage [詳解]
virtual CV_WRAP bool	empty () const
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read [詳解]
virtual CV_WRAP void	save (const String &filename) const
virtual CV_WRAP String	getDefaultName () const

その他の継承メンバ
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]
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

K-nearest neighbours - based Background/Foreground Segmentation Algorithm.

The class implements the K-nearest neighbours background subtraction described in [Zivkovic2006] . Very efficient if number of foreground pixels is low.

関数詳解

getDetectShadows()

virtual CV_WRAP bool cv::BackgroundSubtractorKNN::getDetectShadows ( ) const

pure virtual

Returns the shadow detection flag

If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorKNN for details.

getDist2Threshold()

virtual CV_WRAP double cv::BackgroundSubtractorKNN::getDist2Threshold ( ) const

pure virtual

Returns the threshold on the squared distance between the pixel and the sample

The threshold on the squared distance between the pixel and the sample to decide whether a pixel is close to a data sample.

getkNNSamples()

virtual CV_WRAP int cv::BackgroundSubtractorKNN::getkNNSamples ( ) const

pure virtual

Returns the number of neighbours, the k in the kNN.

K is the number of samples that need to be within dist2Threshold in order to decide that that pixel is matching the kNN background model.

getShadowThreshold()

virtual CV_WRAP double cv::BackgroundSubtractorKNN::getShadowThreshold ( ) const

pure virtual

Returns the shadow threshold

A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiara, Detecting Moving Shadows...*, IEEE PAMI,2003.

getShadowValue()

virtual CV_WRAP int cv::BackgroundSubtractorKNN::getShadowValue ( ) const

pure virtual

Returns the shadow value

Shadow value is the value used to mark shadows in the foreground mask. Default value is 127. Value 0 in the mask always means background, 255 means foreground.

setNSamples()

virtual CV_WRAP void cv::BackgroundSubtractorKNN::setNSamples ( int  _nN )

pure virtual

Sets the number of data samples in the background model.

The model needs to be reinitalized to reserve memory.

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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:

• background_segm.hpp