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| 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.
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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