Bayesian background modeling for foreground detection

VSSN 2005 - Proceedings of the 3rd ACM International Workshop on Video Surveillance and Sensor Networks, co-located with ACM Multimedia 2005

Volumn , Issue , 2005, Pages 55-58

  Porikli, Fatih ^a   Tuzel, Oncel ^b  

^a MITSUBISHI ELECTRIC RESEARCH LABORATORIES   (United States)

^b RUTGERS UNIVERSITY   (United States)

Author keywords

Background generation; Bayesian learning

Indexed keywords

NORMAL DISTRIBUTION; PIXELS; PROBABILITY DISTRIBUTIONS; SECURITY SYSTEMS; SENSOR NETWORKS;

BACKGROUND GENERATIONS; BACKGROUND MODEL; BAYESIAN; BAYESIAN LEARNING; BAYESIAN LEARNING MECHANISM; DYNAMIC SCENES; FOREGROUND DETECTION; MULTI-MODALITY;

LEARNING ALGORITHMS;

EID: 84958699888     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1099396.1099407     Document Type: Conference Paper

References (10)

1. A. Elgammal, D. Harwood, and L. Davis. Non parametric model for background subtraction. In ECCV, pages 751-767, 2000.
2. N. Friedman and S. Russell. Image segmentation in video sequences. In Thirteenth Conf. on Uncertainty in Artificial Intelligence, pages 175-181, 1997.
3. A. Gelman, J. Carlin, H. Stern, and D. Rubin. Bayesian Data Analysis. Chapman and Hall, second edition, 2003.
4. O. Javed, K. Shafique, and M. Shah. A hierarchical approach to robust background subtraction using color and gradient information. In IEEE Workshop on Motion and Video Computing, 2002.
5. K. Karman and A. Von Brandt. Moving object recognition using an adaptive background memory. In Time-Varying Image Processing and Moving Object Recognition, pages 297-307. Elsevier, 1990.
6. L. Li, W. Huang, I. Gu, and Q. Tian. Foreground object detection from videos containing complex background. In ACM Multimedia, 2003.
7. A. Mittal and N. Paragios. Motion-based background subtraction using adaptive kernel density estimation. In CVPR, pages 302-309, 2004.
8. C. Stauffer and E. Grimson. Adaptive background mixture models for real-time tracking. In CVPR, pages 246-252, 1999.
9. K. Toyama, J. Krumm, B. Brumitt, and B. Meyers. Wallflower: principles and practice of background maintenance. In ICCV, pages 255-261, 1999.
10. C. Wren, Azarbayejani, A., T. Darell, and A. Pentland. Pfinder: Real-time tracking of human body. PAMI, 19:780-785, 1997.