A Background Subtraction Library
Last page update: 12/09/2018
Library Version: 2.0.0 (see Build Status and Release Notes for more info)
The BGSLibrary was developed early 2012 by Andrews Sobral to provide an easy-to-use C++ framework (wrappers for Python, Java and MATLAB are also available) for foreground-background separation in videos based on OpenCV. The bgslibrary is compatible with OpenCV 2.x, 3.x and 4.x, and compiles under Windows, Linux, and Mac OS X. Currently the library contains 43 algorithms. The source code is available under GNU GPLv3 license, the library is available free of charge to all users, academic and commercial.
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Installation instructions
You can either install BGSLibrary via pre-built binary package or build it from source:
Supported Compilers are:
GCC 4.8 and above
Clang 3.4 and above
MSVC 2015, 2017
Other compilers might work, but are not officially supported.
If you use this library for your publications, please cite it as:
@inproceedings{bgslibrary,
author = {Sobral, Andrews},
title = {{BGSLibrary}: An OpenCV C++ Background Subtraction Library},
booktitle = {IX Workshop de Visão Computacional (WVC'2013)},
address = {Rio de Janeiro, Brazil},
year = {2013},
month = {Jun},
url = {https://github.com/andrewssobral/bgslibrary}
}
A chapter about the BGSLibrary has been published in the handbook on Background Modeling and Foreground Detection for Video Surveillance.
@incollection{bgslibrarychapter,
author = {Sobral, Andrews and Bouwmans, Thierry},
title = {BGS Library: A Library Framework for Algorithm’s Evaluation in Foreground/Background Segmentation},
booktitle = {Background Modeling and Foreground Detection for Video Surveillance},
publisher = {CRC Press, Taylor and Francis Group.}
year = {2014},
}
Download PDF:
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Sobral, Andrews. BGSLibrary: An OpenCV C++ Background Subtraction Library. IX Workshop de Visão Computacional (WVC'2013), Rio de Janeiro, Brazil, Jun. 2013. (PDF in brazilian-portuguese containing an english abstract).
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Sobral, Andrews; Bouwmans, Thierry. "BGS Library: A Library Framework for Algorithm’s Evaluation in Foreground/Background Segmentation". Chapter on the handbook "Background Modeling and Foreground Detection for Video Surveillance", CRC Press, Taylor and Francis Group, 2014. (PDF in english).
Some algorithms of the BGSLibrary were used successfully in the following papers:
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(2014) Sobral, Andrews; Vacavant, Antoine. A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos. Computer Vision and Image Understanding (CVIU), 2014. (Online) (PDF)
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(2013) Sobral, Andrews; Oliveira, Luciano; Schnitman, Leizer; Souza, Felippe. (Best Paper Award) Highway Traffic Congestion Classification Using Holistic Properties. In International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA'2013), Innsbruck, Austria, Feb 2013. (Online) (PDF)
