| Top |  |  |  |  | 
| gfloat | learning-rate | Read / Write | 
| GstSegmentationMethod | method | Read / Write | 
| gboolean | test-mode | Read / Write | 
GObject ╰── GInitiallyUnowned ╰── GstObject ╰── GstElement ╰── GstBaseTransform ╰── GstVideoFilter ╰── GstOpencvVideoFilter ╰── GstSegmentation
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.htmlbackgroundsubtractormog [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.htmlbackgroundsubtractormog2 [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.
| 1 | gst-launch-1.0 v4l2src device=/dev/video0 ! videoconvert ! segmentation test-mode=true method=2 ! videoconvert ! ximagesink | 
| plugin | opencv | 
| author | Miguel Casas-Sanchez <miguelecasassanchez@gmail.com> | 
| class | Filter/Effect/Video | 
| name | sink | 
| direction | sink | 
| presence | always | 
| details | video/x-raw, format=(string)RGBA, width=(int)[ 1, 2147483647 ], height=(int)[ 1, 2147483647 ], framerate=(fraction)[ 0/1, 2147483647/1 ] | 
| name | src | 
| direction | source | 
| presence | always | 
| details | video/x-raw, format=(string)RGBA, width=(int)[ 1, 2147483647 ], height=(int)[ 1, 2147483647 ], framerate=(fraction)[ 0/1, 2147483647/1 ] | 
“learning-rate” property“learning-rate” gfloat
Speed with which a motionless foreground pixel would become background (inverse of number of frames).
Flags: Read / Write
Allowed values: [0,1]
Default value: 0.01
“method” property  “method”                   GstSegmentationMethod
Segmentation method to use.
Flags: Read / Write
Default value: Mixture-of-Gaussians segmentation (Zivkovic2004)
“test-mode” property“test-mode” gboolean
If true, the output RGB is overwritten with the calculated foreground (white color).
Flags: Read / Write
Default value: FALSE