org.opencv.video

Class BackgroundSubtractorKNN

java.lang.Object

org.opencv.core.Algorithm

org.opencv.video.BackgroundSubtractor

org.opencv.video.BackgroundSubtractorKNN

public class BackgroundSubtractorKNN
extends BackgroundSubtractor

K-nearest neighbours - based Background/Foreground Segmentation Algorithm. The class implements the K-nearest neighbours background subtraction described in CITE: Zivkovic2006 . Very efficient if number of foreground pixels is low.

Field Summary

Fields inherited from class org.opencv.core.Algorithm

nativeObj

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	BackgroundSubtractorKNN(long addr)

Method Summary

Modifier and Type	Method and Description
static BackgroundSubtractorKNN	__fromPtr__(long addr)
protected void	finalize()
boolean	getDetectShadows() Returns the shadow detection flag If true, the algorithm detects shadows and marks them.
double	getDist2Threshold() 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.
int	getHistory() Returns the number of last frames that affect the background model
int	getkNNSamples() Returns the number of neighbours, the k in the kNN.
int	getNSamples() Returns the number of data samples in the background model
double	getShadowThreshold() Returns the shadow threshold A shadow is detected if pixel is a darker version of the background.
int	getShadowValue() Returns the shadow value Shadow value is the value used to mark shadows in the foreground mask.
void	setDetectShadows(boolean detectShadows) Enables or disables shadow detection
void	setDist2Threshold(double _dist2Threshold) Sets the threshold on the squared distance
void	setHistory(int history) Sets the number of last frames that affect the background model
void	setkNNSamples(int _nkNN) Sets the k in the kNN.
void	setNSamples(int _nN) Sets the number of data samples in the background model.
void	setShadowThreshold(double threshold) Sets the shadow threshold
void	setShadowValue(int value) Sets the shadow value

Methods inherited from class org.opencv.video.BackgroundSubtractor

apply, apply, getBackgroundImage

Methods inherited from class org.opencv.core.Algorithm

clear, empty, getDefaultName, getNativeObjAddr, save

Methods inherited from class java.lang.Object

clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

BackgroundSubtractorKNN

protected BackgroundSubtractorKNN(long addr)

Method Detail

__fromPtr__

public static BackgroundSubtractorKNN __fromPtr__(long addr)

getHistory

public int getHistory()

Returns the number of last frames that affect the background model

Returns:

automatically generated

setHistory

public void setHistory(int history)

Sets the number of last frames that affect the background model

Parameters:

history - automatically generated

getNSamples

public int getNSamples()

Returns the number of data samples in the background model

Returns:

automatically generated

setNSamples

public void setNSamples(int _nN)

Sets the number of data samples in the background model. The model needs to be reinitalized to reserve memory.

Parameters:

_nN - automatically generated

getDist2Threshold

public double getDist2Threshold()

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.

Returns:

automatically generated

setDist2Threshold

public void setDist2Threshold(double _dist2Threshold)

Sets the threshold on the squared distance

Parameters:

_dist2Threshold - automatically generated

getkNNSamples

public int getkNNSamples()

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.

Returns:

automatically generated

setkNNSamples

public void setkNNSamples(int _nkNN)

Sets the k in the kNN. How many nearest neighbours need to match.

Parameters:

_nkNN - automatically generated

getDetectShadows

public boolean getDetectShadows()

Returns the shadow detection flag If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorKNN for details.

Returns:

automatically generated

setDetectShadows

public void setDetectShadows(boolean detectShadows)

Enables or disables shadow detection

Parameters:

detectShadows - automatically generated

getShadowValue

public int getShadowValue()

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.

Returns:

automatically generated

setShadowValue

public void setShadowValue(int value)

Sets the shadow value

Parameters:

value - automatically generated

getShadowThreshold

public double getShadowThreshold()

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.

Returns:

automatically generated

setShadowThreshold

public void setShadowThreshold(double threshold)

Sets the shadow threshold

Parameters:

threshold - automatically generated

finalize

protected void finalize()
                 throws Throwable

Overrides:

finalize in class BackgroundSubtractor

Throws:

Throwable