Note: This list of publications comes from my work. Please cite my following paper:
T. Bouwmans, “Background Subtraction For Visual Surveillance: A Fuzzy Approach”, Chapter 5 in Handbook on Soft Computing for Video Surveillance, Taylor and Francis Group, March 2012.
List of Publications on Background Maintenance using Fuzzy Learning Rates (Author: T. Bouwmans, University of La Rochelle, France) (Download in .pdf)
M. Sigari, “Fuzzy Background Modeling/Subtraction and its Application in Vehicle Detection”, World Congress on Engineering and Computer Science, WCECS 2008, San Francisco, USA, October 2008.
M. Sigari, N. Mozayani, H. Pourreza, “Fuzzy Running Average and Fuzzy Background Subtraction: Concepts and Application”, International Journal of Computer Science and Network Security, Volume 8, No. 2, pages 138-143, 2008.
M. Shakeri, H. Deldari, H. Foroughi, A. Saberi, A. Naseri, “A novel fuzzy background subtraction method based on cellular automata for urban traffic applications”, 9th International Conference on Signal Processing, ICSP 2008, pages 899-902, Beijing, China, October 2008.
M. Shakeri, H. Deldari, ”Fuzzy-Cellular Background Subtraction Technique for Urban Traffic Applications”, World Applied Sciences Journal, Volume 5, Issue 1, 2008.
B. Yeo, W. Lim, H. Lim, W. Wong, “Extended fuzzy background modeling for moving vehicle detection using infrared vision”, IEICE Electronics Express, pages 340-345, 2011.
B. Yeo, W. Lim, H. Lim, “Scalable-Width Temporal Edge Detection for Recursive Background Recovery in adaptive background modeling”, Applied Soft Computing, January 2013.
E. Calvo-Gallego, P. Brox, S. Sanchez-Solano, “A Fuzzy System for Background Modeling in Video Sequences”, WILF 2013, pages 184-192, 2013.
L. Maddalena, A. Petrosino, “Multivalued Background/Foreground Separation for Moving Object Detection”, International Workshop on Fuzzy Logic and Applications, WILF 2009, Volume 5571, pages 263-270, Palermo, Italy, June 2009
L. Maddalena, A. Petrosino, “Self Organizing and Fuzzy Modelling for Parked Vehicles Detection”, Advanced Concepts for Intelligent Vision Systems, ACVIS 2009, LNCS 5807, pages 422–433, 2009.
L. Maddalena, A. Petrosino, “A fuzzy spatial coherence-based approach to background/foreground separation for moving object detection”, Neural Computing and Applications, NCA 2009, pages 1-8, 2009.