Class BackgroundSubtractorLSBP


public class BackgroundSubtractorLSBP extends BackgroundSubtractor
Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at CITE: LGuo2016
  • Constructor Details

    • BackgroundSubtractorLSBP

      protected BackgroundSubtractorLSBP(long addr)
  • Method Details

    • __fromPtr__

      public static BackgroundSubtractorLSBP __fromPtr__(long addr)
    • apply

      public void apply(Mat image, Mat fgmask, double learningRate)
      Description copied from class: BackgroundSubtractor
      Computes a foreground mask.
      Overrides:
      apply in class BackgroundSubtractor
      Parameters:
      image - Next video frame.
      fgmask - The output foreground mask as an 8-bit binary image.
      learningRate - The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame.
    • apply

      public void apply(Mat image, Mat fgmask)
      Description copied from class: BackgroundSubtractor
      Computes a foreground mask.
      Overrides:
      apply in class BackgroundSubtractor
      Parameters:
      image - Next video frame.
      fgmask - The output foreground mask as an 8-bit binary image. learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame.
    • apply

      public void apply(Mat image, Mat knownForegroundMask, Mat fgmask, double learningRate)
      Description copied from class: BackgroundSubtractor
      Computes a foreground mask with known foreground mask input.
      Overrides:
      apply in class BackgroundSubtractor
      Parameters:
      image - Next video frame. Floating point frame will be used without scaling and should be in range \([0,255]\).
      knownForegroundMask - The mask for inputting already known foreground, allows model to ignore pixels.
      fgmask - The output foreground mask as an 8-bit binary image.
      learningRate - The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame. Note: This method has a default virtual implementation that throws a "not impemented" error. Foreground masking may not be supported by all background subtractors.
    • apply

      public void apply(Mat image, Mat knownForegroundMask, Mat fgmask)
      Description copied from class: BackgroundSubtractor
      Computes a foreground mask with known foreground mask input.
      Overrides:
      apply in class BackgroundSubtractor
      Parameters:
      image - Next video frame. Floating point frame will be used without scaling and should be in range \([0,255]\).
      knownForegroundMask - The mask for inputting already known foreground, allows model to ignore pixels. learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame. Note: This method has a default virtual implementation that throws a "not impemented" error. Foreground masking may not be supported by all background subtractors.
      fgmask - The output foreground mask as an 8-bit binary image.
    • getBackgroundImage

      public void getBackgroundImage(Mat backgroundImage)
      Description copied from class: BackgroundSubtractor
      Computes a background image.
      Overrides:
      getBackgroundImage in class BackgroundSubtractor
      Parameters:
      backgroundImage - The output background image. Note: Sometimes the background image can be very blurry, as it contain the average background statistics.