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  Maitre de Conférences (HDR)                                                                       
  Laboratoire MIA
 
La Rochelle Université
  17000 La Rochelle
  France
  tbouwman at univ-lr.fr





Events


Third Workshop "Robust Subspace Learning and Computer Vision", RSL-CV 2019 in conjunction with ICCV 2019, October 2019. (More information)

Special Issue on “Robust Subspace Learning and Tracking: Theory, Algorithms, and Applications”, IEEE Journal of Selected Topics in Signal Processing December 2018 (More information)

Special Issue on “Rethinking PCA for Modern Datasets: Theory, Algorithms, and Applications”, Proceedings of the IEEE,  July 2018. (More information) [Accompanying website]


Research Interests


My research interests in computer vision consist mainly in the detection of moving objects in challenging surface (ground and sea), air and space environments.

For detection of moving foreground objects in surface environments, my research focus on background subtraction (Background Subtraction Research). In this research, I investigated particularly the application of different mathematical concepts (statistical, fuzzy and Dempster-Schafer) as well as machine learning concepts (reconstructive and discriminative subspace learning models, robust PCA and deep neural networks) in video surveillance.

My work also concerns full exhaustive surveys on mathematical and machine learning tools used in foreground/background separation. Furthermore, I investigated the field of decomposition into low-rank and additives matrices for background/foreground separation (DLAM Research), the field of decomposition into low-rank and additives tensors for background/foreground separation (DLAT research), and the field of decomposition into sparse and additive matrices for background/foreground separation (DSAM research).

My research concerns also robust texture features and feature selection for background/foreground separation (Features Research).

Key words: Background subtraction, fuzzy concepts, Dempster-Schafer theory, Robust Principal Component Analysis, deep neural networks, LBP features.


Recent Publications


T. Bouwmans, S. Javed, M. Sultana, S. Jung, “Deep Neural Network Concepts in Background Subtraction: A Systematic Review and A Comparative Evaluation”, Neural Networks, 2019.

T. Bouwmans, B. Garcia-Garcia, "Background Subtraction in Real Applications: Challenges, Current Models and Future Directions", Submitted to Computer Science Review, 2019.


My recent publications are available on Academia, Research Gate, Researchr, ORCID, ResearchID and Publication List.