1. Sébastien Piérard, Marc Braham, and Marc Van Droogenbroeck. An exploration of the performances achievable by combining unsupervised background subtraction algorithms. ArXiv, abs/2202.12563, February 2022. Keyword(s): Background subtraction, Combination, Majority vote, BKS, Evaluation, Performance, Summarization, Change detection, Classification performance, CDNet 2014, ARIAC. [bibtex-entry]



2. Anthony Cioppa, Marc Braham, and Marc Van Droogenbroeck. Asynchronous semantic background subtraction. Journal of Imaging, 6(50):1-20, June 2020. Keyword(s): Background subtraction, Real time, Change detection, Semantic segmentation, Semantic background subtraction, CDNet 2014, DeepSport. [bibtex-entry]

1. Anthony Cioppa, Marc Van Droogenbroeck, and Marc Braham. Real-Time Semantic Background Subtraction. In IEEE International Conference on Image Processing (ICIP), Abu Dhabi, United Arab Emirates, pages 3214-3218, October 2020. Keyword(s): Background subtraction, Real time, Change detection, Semantic segmentation, Semantic background subtraction, DeepSport, CDNet 2014. [bibtex-entry]



2. Sébastien Piérard and Marc Van Droogenbroeck. Summarizing the performances of a background subtraction algorithm measured on several videos. In IEEE International Conference on Image Processing (ICIP), Abu Dhabi, United Arab Emirates, pages 3234-3238, October 2020. Keyword(s): Background subtraction, Evaluation, Performance, Summarization, Change detection, Classification performance, CDNet 2014, DeepSport. [bibtex-entry]



3. Marc Braham, Sébastien Piérard, and Marc Van Droogenbroeck. Semantic Background Subtraction. In IEEE International Conference on Image Processing, Beijing, China, pages 4552-4556, September 2017. Keyword(s): Background subtraction, Change detection, Semantic segmentation, Scene labeling, Scene parsing, Classification, Machine learning, Deep learning, CDNet 2014. [bibtex-entry]



4. Marc Braham and Marc Van Droogenbroeck. Deep Background Subtraction with Scene-Specific Convolutional Neural Networks. In International Conference on Systems, Signals and Image Processing (IWSSIP), Bratislava, Slovakia, pages 1-4, May 2016. Keyword(s): Background subtraction, Deep learning, Machine learning, CDNet, Change detection, CDNet 2014. [bibtex-entry]

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All person copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.