Background subtraction based on a combination of texture, color and intensity

International Conference on Signal Processing Proceedings, ICSP

Volumn , Issue , 2008, Pages 1400-1405

  Jian, Xu ^a   Xiao Qing, Ding ^a   Sheng Jin, Wang ^a   You Shou, Wu ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BACKGROUND SUBTRACTION; BACKGROUND SUBTRACTION ALGORITHMS; CAST SHADOW; COLOR SPACE; COMPARATIVE EXPERIMENTS; INTENSITY INFORMATION; PIXEL INTENSITIES; TEXTURE AREA;

SIGNAL PROCESSING; TEXTURES;

COLOR;

EID: 67249125050     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICOSP.2008.4697394     Document Type: Conference Paper

References (13)

1. C. Stauffer and W. Grimson. Adaptive Background Mixture Models for Real-time Tracking. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 23-25, June 1999.
2. O. Tuzel, F. Porikli, and P. Meer. A Bayesian Approach to Background Modeling. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 3, pp 58, June 2005.
3. A. Elgammal, R. Duraiswami, D. Harwood, and L. S. Davis. Background and Foreground Modeling Using Nonparametric Kernel Density Estimation for Visual Surveillance. Proc. IEEE, vol. 90, no. 7, pp. 1151-1163, 2002.
4. V. Jain, B.-B. Kimia, J.- L. Mundy. Background Modeling Based on Subpixel Edges. IEEE Int'l Conf. on Image Processing, vol. 6, pp. 321-324, Oct. 2007.
5. C.-R. Wren, A. Azarbayejani, T. Darrell, and A.-P. Pentland. Pfinder: Real-Time Tracking of the Human Body. IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 780-785, July 1997.
6. A. Monnet, A. Mittal, N. Paragios, and R. Visvanathan. Background Modeling and Subtraction of Dynamic Scenes. Proc. IEEE Int'l Conf. Computer Vision, vol. 2, pp. 1305-1312, 2003.
7. M. Mason and Z. Duric. Using Histograms to Detect and Track Objects in Color Video. Proc. Applied Imagery Pattern Recognition Workshop, pp. 154-159, 2001.
8. T. Matsuyama, T. Ohya, and H. Habe. Background Subtraction for Non-Stationary Scenes. Proc. Asian Conf. Computer Vision, pp. 622-667, 2000.
9. M. Heikkila and M. Pietikainen. A texture-based method for modeling the background and detecting moving objects. IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 28, pp. 657-662, April 2006.
10. K. Toyama, J. Krumm, B. Brumitt, and B. Meyers. Wallflower: Principles and Practice of Background Maintenance. Proc. IEEE Int'l Conf. Computer Vision, vol. 1, pp. 255-261, 1999.
11. H. Nakai. Non-Parameterized Bayesian Decision Method for Moving Object Detection. Proc. Asian Conf. Computer Vision. 1995. Singapore.
12. N. Oliver, B. Rosario, and A. Pentland. A Bayesian Computer Vision System for Modeling Human Interactions. Proc. Int'l Conf. on Vision Systems. 1999. Gran Canaria, Spain: Springer.
13. H. Kim, R. Sakamoto, I. Kitahara, T. Toriyama and K. Kogure. Background Subtraction Using Generalised Gaussian Family Model. IEEE Electronics Letters. Vol. 44, no. 3, pp. 189-190, Jan. 2008.