[Bug 701421] New: opencv: add foreground/background segmentation element

[GStreamer (bugzilla.gnome.org)]

https://bugzilla.gnome.org/show_bug.cgi?id=701421
  GStreamer | gst-plugins-bad | 1.x

           Summary: opencv: add foreground/background segmentation element
    Classification: Platform
           Product: GStreamer
           Version: 1.x
        OS/Version: All
            Status: UNCONFIRMED
          Severity: enhancement
          Priority: Normal
         Component: gst-plugins-bad
        AssignedTo: gstreamer-bugs at lists.freedesktop.org
        ReportedBy: miguelecasassanchez at gmail.com
         QAContact: gstreamer-bugs at lists.freedesktop.org
     GNOME version: ---


Created an attachment (id=245821)
 View: https://bugzilla.gnome.org/attachment.cgi?id=245821
 Review: https://bugzilla.gnome.org/review?bug=701421&attachment=245821

Segmentation plugin and associated opencv c++ wrapper.

Add an element to the opencv plugin for foregroung/background image sequence
segmentation, using one out of 3 algorithms. The patch includes a c++ mini
wrapper, for the OpenCV functions only available with this language bindings.

In the C file documentation there's more information on the algorithms and
their origins:

 * 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 Gausian 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.
 *

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