Class BackgroundSubtractor

java.lang.Object
org.opencv.core.Algorithm
org.opencv.video.BackgroundSubtractor
Direct Known Subclasses:
BackgroundSubtractorCNT, BackgroundSubtractorGMG, BackgroundSubtractorGSOC, BackgroundSubtractorKNN, BackgroundSubtractorLSBP, BackgroundSubtractorMOG, BackgroundSubtractorMOG2
public class BackgroundSubtractor extends Algorithm
Base class for background/foreground segmentation. : The class is only used to define the common interface for the whole family of background/foreground segmentation algorithms.

  • Constructor Details

    • BackgroundSubtractor

      protected BackgroundSubtractor(long addr)

  • Method Details

    • __fromPtr__

      public static BackgroundSubtractor __fromPtr__(long addr)

    • apply

      public void apply(Mat image, Mat fgmask, double learningRate)
      Computes a foreground mask.
      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)
      Computes a foreground mask.
      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)
      Computes a foreground mask with known foreground mask input.
      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)
      Computes a foreground mask with known foreground mask input.
      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)
      Computes a background image.
      Parameters:
      backgroundImage - The output background image. Note: Sometimes the background image can be very blurry, as it contain the average background statistics.