Skip to main content

BGSLibrary

A Background Subtraction Library

Release License: GPL v3 Platform: Windows, Linux, OS X OpenCV Wrapper: Python, MATLAB Algorithms

bgslibrary

Last page update: 06/08/2019

Library Version: 3.0.0 (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 2.4.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 the MIT license, the library is available free of charge to all users, academic and commercial.

You can either install BGSLibrary via pre-built binary package or build it from source via:

git clone --recursive https://github.com/andrewssobral/bgslibrary.git

Supported Compilers are:

GCC 4.8 and above
Clang 3.4 and above
MSVC 2015, 2017, 2019

Other compilers might work, but are not officially supported. The bgslibrary requires some features from the ISO C++ 2014 standard.

Citation

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:

  • 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).

  • 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 references

Some algorithms of the BGSLibrary were used successfully in the following papers:

  • (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)

  • (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)

Videos

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pybgs-3.0.0.post0.tar.gz (835.4 kB view details)

Uploaded Source

File details

Details for the file pybgs-3.0.0.post0.tar.gz.

File metadata

  • Download URL: pybgs-3.0.0.post0.tar.gz
  • Upload date:
  • Size: 835.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.19.1 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.6

File hashes

Hashes for pybgs-3.0.0.post0.tar.gz
Algorithm Hash digest
SHA256 6989612bb1bdb61f48d1f516d850a07d90ffe416777d1dd79f9db7d259c4defb
MD5 8b65c0d980f6409b9b77fb010a8f1095
BLAKE2b-256 4a242ebcdc6d43fcabe5b75dcb27f3aa48a0dd3a8a4581ca7a686aa18704acc3

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page