Special Session on "Dynamic Background Reconstruction/Subtraction for Challenging Environments” in conjunction with ICIP 2020, October 2020 (more information)
Workshop on “Sensors in Target Detection”, STD 2020 in conjunction with WiSEE 2020, Vicenza, Italy, October 2020. (More information)
Special issue on "Neural Computing for IOT based Intelligent Healthcare Systems", Neural Computing and Application, to appear in 2021. (More information)
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 and air 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 theories), machine learning concepts (reconstructive and discriminative subspace learning models, robust PCA and deep neural networks), and signal processing concepts (signal graph processing) 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).
M. Chapel, T. Bouwmans, "Moving Objects Detection with a Moving Camera: A Comprehensive Review", Computer Science Review, Volume 38, November 2020.
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.
B. Garcia-Garcia, T. Bouwmans, A. Rosales-Silva, "Background Subtraction in Real Applications: Challenges, Current Models and Future Directions", Computer Science Review, Volume 35, February 2020.