Background subtraction is one of the most active research topics in computer vision due to manypotential applications including surveillance devices in public spaces, traffic monitoring and industrial machine vision . Researchers have been working for decades to develop methods to handle the different type of challenges, such as bad weather, noise, shadow, etc. However, at the present time, no algorithm seems to be able to simultaneously address all the key challenges found in real environments.
In this context, the aim of this workshop is first to present an overview of the existing and recent developments, and global perspectives to handle the remained unsolved challenges. Second, we will present recent developments with RPCA  and feature selection . Third, the BGSLibrary and LBPLibrary will be presented with the two large-scale datasets ChangeDetection.net and BMC 2012 dataset.
To be developed
 Handbook on “Background Modeling and Foreground Detection for Video Surveillance”, CRC Press, Taylor and Francis Group, July 2014.
 Handbook on “Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video”, CRC Press, Taylor and Francis Group, May 2016.
 T. Bouwmans, A. Sobral, S. Javed, S. Jung, E. Zahzah, "Decomposition into Low-rank plus Additive Matrices for Background/Foreground Separation: A Review for a Comparative Evaluation with a Large-Scale Dataset", Computer Science Review, Volume 23, pages 1-71, February 2017.
T. Bouwmans, “Traditional and Recent Approaches in Background Modeling for Foreground Detection: An Overview”, Computer Science Review, Volume 11, pages 31-66, May 2014.
 C. Silva, T. Bouwmans, C. Frelicot, "Online Weighted One-Class Ensemble for Feature Selection in Background/Foreground Separation", International Conference on Pattern Recognition, ICPR 2016, December 2016.
 Background Subtraction Website (T. Bouwmans, Lab. MIA, Univ. La Rochelle, France)