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opencv_contrib/modules/bgsegm
Alexander Alekhin 62e77e9945
build: fix usage of unsupported cv::Mat types 		8 years ago
..
doc Doxygen documentation for all modules 10 years ago
include/opencv2 bgsegm(docs): information about author of BackgroundSubtractorCNT 8 years ago
samples bgsegm: update sample 8 years ago
src build: fix usage of unsupported cv::Mat types 8 years ago
test added outflow, bgsegm modules; moved matlab from the main repository 11 years ago
CMakeLists.txt Reduced modules dependencies: 8 years ago
README.md Merge pull request #493 from kiranpradeep:bg_segm_documentation_fix 8 years ago

README.md

Improved Background-Foreground Segmentation Methods

This algorithm combines statistical background image estimation and per-pixel Bayesian segmentation. It[1] was introduced by Andrew B. Godbehere, Akihiro Matsukawa, Ken Goldberg in 2012. As per the paper, the system ran a successful interactive audio art installation called “Are We There Yet?” from March 31 - July 31 2011 at the Contemporary Jewish Museum in San Francisco, California.

It uses first few (120 by default) frames for background modelling. It employs probabilistic foreground segmentation algorithm that identifies possible foreground objects using Bayesian inference. The estimates are adaptive; newer observations are more heavily weighted than old observations to accommodate variable illumination. Several morphological filtering operations like closing and opening are done to remove unwanted noise. You will get a black window during first few frames.

References

[1]: A.B. Godbehere, A. Matsukawa, K. Goldberg. Visual tracking of human visitors under variable-lighting conditions for a responsive audio art installation. American Control Conference. (2012), pp. 4305–4312