Class 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.
    • Constructor Detail

      • BackgroundSubtractorKNN

        protected BackgroundSubtractorKNN​(long addr)
    • Method Detail

      • getDetectShadows

        public boolean getDetectShadows()
        Returns the shadow detection flag If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorKNN for details.
        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.
        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.
        automatically generated
      • getHistory

        public int getHistory()
        Returns the number of last frames that affect the background model
        automatically generated
      • getNSamples

        public int getNSamples()
        Returns the number of data samples in the background model
        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.
        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.
        automatically generated
      • setDetectShadows

        public void setDetectShadows​(boolean detectShadows)
        Enables or disables shadow detection
        detectShadows - automatically generated
      • setDist2Threshold

        public void setDist2Threshold​(double _dist2Threshold)
        Sets the threshold on the squared distance
        _dist2Threshold - automatically generated
      • setHistory

        public void setHistory​(int history)
        Sets the number of last frames that affect the background model
        history - 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.
        _nN - automatically generated
      • setShadowThreshold

        public void setShadowThreshold​(double threshold)
        Sets the shadow threshold
        threshold - automatically generated
      • setShadowValue

        public void setShadowValue​(int value)
        Sets the shadow value
        value - automatically generated
      • setkNNSamples

        public void setkNNSamples​(int _nkNN)
        Sets the k in the kNN. How many nearest neighbours need to match.
        _nkNN - automatically generated
      • finalize

        protected void finalize()
                         throws java.lang.Throwable
        finalize in class BackgroundSubtractor