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Publications of Marc Braham
Articles in journal or book chapters
  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]


Conference articles
  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. 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]


  3. 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]


  4. Marc Braham and Marc Van Droogenbroeck. A generic feature selection method for background subtraction using global foreground models. In Advanced Concepts for Intelligent Vision Systems (ACIVS), volume 9386 of Lecture Notes in Computer Science, pages 717-728, 2015. Keyword(s): Background subtraction, Feature selection, Foreground model, Change detection, ViBe. [bibtex-entry]


  5. Benjamin Laugraud, Sébastien Piérard, Marc Braham, and Marc Van Droogenbroeck. Simple median-based method for stationary background generation using background subtraction algorithms. In International Conference on Image Analysis and Processing (ICIAP), Workshop on Scene Background Modeling and Initialization (SBMI), volume 9281 of Lecture Notes in Computer Science, pages 477-484, 2015. Note: Source code in C++ available. Keyword(s): Background subtraction, Background image, Source code. [bibtex-entry]


  6. Marc Braham, Antoine Lejeune, and Marc Van Droogenbroeck. A physically motivated pixel-based model for background subtraction in 3D images. In IEEE International Conference on 3D Imaging (IC3D), Liège, Belgium, pages 1-8, December 2014. Keyword(s): Background subtraction, 3D, Range, Depth, Kinect. [bibtex-entry]


Miscellaneous
  1. Marc Van Droogenbroeck, Marc Braham, and Sébastien Piérard. Foreground and background detection method. Chinese Patent Office, CN 109389618 B2, 18 pages, March 2022. Keyword(s): Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence. [bibtex-entry]


  2. Marc Van Droogenbroeck, Marc Braham, and Anthony Cioppa. Foreground and background detection method. United States Patent and Trademark Office, US 10,706,558 B2, 26 pages, July 2020. Keyword(s): Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence, DeepSport. [bibtex-entry]


  3. Marc Van Droogenbroeck, Marc Braham, and Sébastien Piérard. Foreground and background detection method. European Patent Office, EP 3438929 B2, July 2020. Keyword(s): Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence. [bibtex-entry]


  4. Marc Van Droogenbroeck, Marc Braham, and Sébastien Piérard. Foreground and background detection method. United States Patent and Trademark Office, US 10614736 B2, 16 pages, April 2020. Keyword(s): Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence. [bibtex-entry]


  5. Marc Van Droogenbroeck, Marc Braham, and Sébastien Piérard. Foreground and background detection method. Chinese Patent Office, CN109389618A, February 2019. Keyword(s): Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence. [bibtex-entry]



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