The aim of this web site is to provide ressources such as references (539 papers) , codes and links to demonstration websites for the research on robust features for background/foreground separation by grouping all related researches and particularly recent advances in this field.
T . Bouwmans, "Features Website", Laboratoire MIA, Univ. of La Rochelle, June 2016.
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This web site presents a survey on robust features for background/foreground separation. If you use information from this web site for publication, please cite the following papers:
C. Silva, T. Bouwmans, C. Frelicot, "An eXtended Center-Symmetric Local Binary Pattern for Background Modeling and Subtraction in Videos", VISAPP 2015, Berlin, Germany, March 2015.
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.
C. Pacheco, T. Bouwmans, C. Frelicot, "Superpixel-based online wagging one-class ensemble for feature selection in foreground/background separation", Pattern Recognition Letters, 2017.
T. Bouwmans, C. Silva, C. Marghes, M. Zitouni, H. Bhaskar, C. Frelicot, “On the Role and the Importance of Features for Background Modeling and Foreground Detection”, Computer Science Review, Volume 28, pages 26-91, May 2018.