Type-2 Fuzzy Mixture of Gaussians (T2-FMOG)

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 Modeling using Type-2 Fuzzy Mixture of Gaussians

F. El Baf, T. Bouwmans, B. Vachon, “Type-2 Fuzzy Mixture of Gaussians Model: Application to Background Modeling”, International Symposium on Visual Computing, ISVC 2008, pages 772-781, Las Vegas, USA, December 2008.

F. El Baf, T. Bouwmans, B. Vachon, “Fuzzy Statistical Modeling of Dynamic Backgrounds for Moving Object Detection in Infrared Videos”, OTCBVS 2009, pages 60-65, Miami, Florida, June 2009.

T. Bouwmans, F. El Baf, “Modeling of Dynamic Backgrounds by Type-2 Fuzzy Gaussians Mixture Models”, MASAUM Journal of Basic and Applied Sciences, Volume 1, Issue 2, 2009.

Z. Zhao, T. Bouwmans, X. Zhang, Y. Fang, “A Fuzzy Background Modeling Approach for Motion Detection in Dynamic Backgrounds”, International Conference on Multimedia and Signal Processing, Shanghai, China, December 2012

Y. Guo, Y. Ji, J. Zhang, S. Gong, C. Liu, “Robust Dynamic Background Model with Adaptive Region Based on T2FS and GMM”, Knowledge Science, Engineering and Management, pages 764-770, 2015.

A. Darwich, P. Hebert, Y. Mohanna, A. Bigand, "Background Subtraction under Uncertainty using a Type-2 Fuzzy Set Gaussian Mixture Model", International Conference on Computer Science, Computer Engineering, and Education Technologies, CSCEET 2017, pages 1-6, April 2017.

A. Darwich, P. Hebert, Y. Mohanna, A. Bigand, "Background Subtraction Based on a New Fuzzy Mixture of Gaussians for Moving Object Detection", MDPI Journal of Imaging, 2018.