We recommend an Open Source library for background modeling.

Source: Internet
Author: User

From: http://blog.csdn.net/carson2005/article/details/8861685

For example, the library named bgslibrary is an open-source library written in C ++ for the background of background subtraction (BGS) minus related algorithms. It contains 29 common background subtraction algorithms. Currently released on Google
Above the code, the link is: https://code.google.com/p/bgslibrary/, which complies with the gnu gpl V3 protocol and can be downloaded by friends. Currently, this library includes the following BGS algorithms:

Basic Methods, mean and variance over time:
(Staticframedifferencebgs) Static Frame Difference
(Framedifferencebgs) Frame Difference
(Weightedmovingmeanbgs) Weighted Moving mean
(Weightedmovingvariancebgs) Weighted Moving Variance
(Adaptivebackgroundlearning) Adaptive Background Learning
1 (dpmeanbgs) Temporal mean
1 (dpadaptivemedianbgs) Adaptive medianOf McFarlane and scholar Field
(1995) Paper Link
1 (dppratimediodbgs) Temporal MedianOf cucchiara et al (2003)
And calderara et al (2006) Paper link1 paper
Link2 paper link3

Fuzzy Based Methods:
2 (fuzzysugenointegral) Fuzzy Sugeno Integral(With Adaptive-selective
Update) of Hongxun Zhang and de Xu (2006) Paper Link
2 (fuzzychoquetintegral) Fuzzy Choquet Integral(With Adaptive-selective
Update) of BAF et al (2008) Paper Link
3 (lbfuzzygaussian) Fuzzy GaussianOf sigari et al (2008) Paper
Link

Statistical methods using one Gaussian:
1 (dpwrengabgs) Gaussian averageOf Wren (1997) Paper
Link
3 (lbsimplegaussian) Simple gaussianOf benezeth et al (2008) Paper
Link

Statistical methods using multiple gaussians:
1 (dpgrimsongmmbgs) Gaussian Mixture ModelOf stauffer and Grimson
(1999) Paper Link
0 (mixtureofgaussianv1bgs) Gaussian Mixture ModelOf kadewtrakupong
And bowden (2001) Paper Link
0 (mixtureofgaussianv2bgs) Gaussian Mixture ModelOf Zivkovic
(2004) Paper link1 paper
Link2
1 (dpzivkovicagmmbgs) Gaussian Mixture ModelOf ZIVKOVIC (2004) Paper
Link1 paper link2

3 (lbmixtureofgaussians) Gaussian Mixture ModelOf BAF et al
(2008) Paper Link

Type-2 fuzzy based methods:
2 (t2fgmm_um) Type-2 fuzzy GMM-UMOf BAF et al (2008) Paper
Link
2 (t2fgmm_uv) Type-2 fuzzy GMM-UVOf BAF et al (2008) Paper
Link
2 (t2fmrf_um) Type-2 fuzzy GMM-UM with MRFOf Zhao et al (2012) Paper
Link1 paper link2

2 (t2fmrf_uv) Type-2 fuzzy GMM-UV with MRFOf Zhao et al (2012) Paper
Link1 paper link2

Statistical methods using color and texture features:
4 (multilayerbgs) Multi-layer BGSOf Jian Yao and Jean-Marc odobez
(2007) Paper Link

Non-parametric methods:
5 (pixelbasedadaptivesegmenter) Pixel-based adaptive segmenter (PBAs)Of
Hofmann et al (2012) Paper Link
0 (GMG) GMGOf godbehere et al (2012) Paper
Link
6 (vumeter) VumeterOf goyat et al (2006) Paper
Link

Methods Based on eigenvalues and eigenvectors:
1 (dpeigenbackgroundbgs) Eigenbackground/SL-PCAOf Oliver et
Al (0, 2000) Paper Link

Neural and neuro-fuzzy methods:
3 (lbadaptivesom) Adaptive SOMOf Maddalena and petrosino (2008) Paper
Link
3 (lbfuzzyadaptivesom) Fuzzy Adaptive SOMOf Maddalena and petrosino
(2010) Paper Link

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