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Showing content from https://gstreamer.freedesktop.org/documentation/opencv/segmentation.html below:

segmentation

This element creates and updates a fg/bg model using one of several approaches. The one called "codebook" refers to the codebook approach following the opencv O'Reilly book [1] implementation of the algorithm described in K. Kim, T. H. Chalidabhongse, D. Harwood and L. Davis [2]. BackgroundSubtractorMOG [3], or MOG for shorts, refers to a Gaussian Mixture-based Background/Foreground Segmentation Algorithm. OpenCV MOG implements the algorithm described in [4]. BackgroundSubtractorMOG2 [5], refers to another Gaussian Mixture-based Background/Foreground segmentation algorithm. OpenCV MOG2 implements the algorithm described in [6] and [7].

[1] Learning OpenCV: Computer Vision with the OpenCV Library by Gary Bradski and Adrian Kaehler, Published by O'Reilly Media, October 3, 2008 [2] "Real-time Foreground-Background Segmentation using Codebook Model", Real-time Imaging, Volume 11, Issue 3, Pages 167-256, June 2005. [3] http://opencv.itseez.com/modules/video/doc/motion_analysis_and_object_tracking.html#backgroundsubtractormog [4] P. KadewTraKuPong and R. Bowden, "An improved adaptive background mixture model for real-time tracking with shadow detection", Proc. 2nd European Workshop on Advanced Video-Based Surveillance Systems, 2001 [5] http://opencv.itseez.com/modules/video/doc/motion_analysis_and_object_tracking.html#backgroundsubtractormog2 [6] Z.Zivkovic, "Improved adaptive Gaussian mixture model for background subtraction", International Conference Pattern Recognition, UK, August, 2004. [7] Z.Zivkovic, F. van der Heijden, "Efficient Adaptive Density Estimation per Image Pixel for the Task of Background Subtraction", Pattern Recognition Letters, vol. 27, no. 7, pages 773-780, 2006.

 gst-launch-1.0  v4l2src device=/dev/video0 ! videoconvert ! segmentation test-mode=true method=2 ! videoconvert ! ximagesink

Authors: – Miguel Casas-Sanchez

Classification: – Filter/Effect/Video

Rank – none

Plugin – opencv

Package – GStreamer Bad Plug-ins

video/x-raw:
         format: RGBA
          width: [ 1, 2147483647 ]
         height: [ 1, 2147483647 ]
      framerate: [ 0/1, 2147483647/1 ]

Presence – always

Direction – sink

Object type – GstPad

video/x-raw:
         format: RGBA
          width: [ 1, 2147483647 ]
         height: [ 1, 2147483647 ]
      framerate: [ 0/1, 2147483647/1 ]

Presence – always

Direction – src

Object type – GstPad

“learning-rate” gfloat

Speed with which a motionless foreground pixel would become background (inverse of number of frames)

Flags : Read / Write

Default value : 0.01

“method” Segmentation-method *

Segmentation method to use

Flags : Read / Write

Default value : mog2 (2)

“test-mode” gboolean

If true, the output RGB is overwritten with the calculated foreground (white color)

Flags : Read / Write

Default value : false

codebook (0) – Codebook-based segmentation (Bradski2008)

mog (1) – Mixture-of-Gaussians segmentation (Bowden2001)

mog2 (2) – Mixture-of-Gaussians segmentation (Zivkovic2004)

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