GitHub - xiaoyan-hou/emvisi2: Background subtraction robust to illumination changes

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Background subtraction robust to illumination changes

GPL-3.0 license

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Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
data		data
.gitignore		.gitignore
CMakeLists.txt		CMakeLists.txt
LICENSE.txt		LICENSE.txt
README		README
emvisi2.cpp		emvisi2.cpp
emvisi2.h		emvisi2.h
emvisi2_test.cpp		emvisi2_test.cpp
emvisi2_video.cpp		emvisi2_video.cpp
fwncc.cpp		fwncc.cpp
fwncc.h		fwncc.h
growmat.cpp		growmat.cpp
growmat.h		growmat.h
imstat.h		imstat.h
learn.cpp		learn.cpp
ncc_proba.cpp		ncc_proba.cpp

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This code illustrates the following paper:

	Making Background Subtraction Robust to Sudden Illumination Changes,
	Julien Pilet, Christoph Strecha and Pascal Fua, 
       	European Conference on Computer Vision, Marseille, France, October 2008.
	
The package contains two programs: emvisi2 and learn. "emvisi2" segments
foreground and background. "learn" takes a set of background/input/ground truth
triplets to estimate the behavior of NCC on your data. The resulting histograms
are saved in several files, including ncc_proba.cpp which emvisi2 uses.

A default ncc_proba.cpp is provided. Expect performance improvement if one
adapted to your own data.

You can optionally smooth the result with a graphcut. Have a look at the
Makefile.

If you have trouble compiling fwncc.cpp, try with the -msse2 compiler flag.

Please respect the GPL terms.

Good luck !
Julien Pilet. November 2008.