Robust techniques for background subtraction in urban traffic video

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5308, Issue PART 2, 2004, Pages 881-892

  Cheung, Sen Ching S ^a   Kamath, Chandrika ^a  

^a LAWRENCE LIVERMORE NATIONAL LABORATORY   (United States)

Author keywords

Background subtraction; Urban traffic video

Indexed keywords

BACKGROUND SUBTRACTION; PROBABILISTIC MODELING; ROBUST TECHNIQUES; URBAN TRAFFIC VIDEO;

ALGORITHMS; CAMERAS; INFORMATION ANALYSIS; KALMAN FILTERING; MOTION ESTIMATION; PATTERN RECOGNITION; PROBLEM SOLVING; STATISTICAL METHODS;

COMPUTER VISION;

EID: 10444271708     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.526886     Document Type: Conference Paper

References (34)

1. A. Mittal and D. Huttenlocher, "Scene modeling for wide area surveillancd and image synthesis," in Proceedings IEEE conference on computer vision and pattern recognition, 2, pp. 160-167, (Hilton Head Isand, SC), June 2000.
2. J. Kang, I. Cohen, and G. Medioni, "Continuous tracking within and across camera streams," in Proceedings IEEE conference on computer vision and pattern recognition, 1, pp. 267-272, (Madison, WI), June 2003.
3. C. Wren, A. Azabayejani, T. Darrel, and A. Pentland, "Pfinder: Real-time tracking of the human body," IEEE Transactions on Pattern Analysis and Machine Intelligence 19, pp. 780-785, July 1997.
4. R. Cutler and L. Davis, "View-based detection," in Proceedings Fourteenth International Conference on Pattern Recognition, 1, pp. 495-500, (Brisbane, Australia), Aug 1998.
5. A. Elgammal, D. Harwood, and L. Davis, "Non-parametric model for background subtraction," in Proceedings of IEEE ICCV'99 Frame-rate workshop, Sept 1999.
6. C. Stauffer and W. Grimson, "Learning patterns of activity using real-time tracking,'' in IEEE Trans. on Pattern Analysis and Machine Intelligence, 22, pp. 747-57, Aug 2000.
7. P. Kaew TraKulPong and R. Bowden, ''An improved adaptive background mixture model for real-time tracking with shadow detection," in Proceedings of the 2nd European Workshop on Advanced Video-Based Surveillance Systems, Sept. 2001.
8. M. Harville, "A framework for high-level feedback to adaptive, per-pixel, mixture-of-Gaussian background models," in Proceedings of the Seventh European Conference on Computer Vision, Part III, pp. 543-60, (Copenhagen, Denmark), May 2002.
9. D. R. Magee, "Tracking multiple vehicles using foreground, background, and motion models," in Proceedings of the Statistical Methods in Video Processing Workshop, pp. 7-12, (Copenhagen, Denmark), June 2002.
10. R. Cucchiara, M. Piccardi, and A. Prati, "Detecting moving objects, ghosts, and shadows in video streams," IEEE Transactions on Pattern Analysis and Machine Intelligence 25, pp. 1337-1342, Oct 2003.
11. D. Koller, J. Weber, and J. Malik, "Robust multiple car tracking with occlusion reasoning," Tech. Rep. UCB/CSD-93-780, EECS Department, University of California, Berkeley, Oct 1993.
12. R. Pless, J. Larson, S. Siebers, and B. Westover, "Evaluation of local models of dynamic background," in Proceedings IEEE conference on computer vision and pattern recognition, 2, pp. 73-78, (Madison, WI), June 2003.
13. N. Oliver, B. Rosario, and A. Pentland, "A Bayesian computer vision system for modeling human interactions," IEEE Transactions on Pattern Analysis and Machine Intelligence 22, pp. 831-843, Aug 2000.
14. 4: real-time surveillance of people and their activities," IEEE Transactions on Pattern Analysis and Machine Intelligence 22, pp. 809-830, Aug 2000.
15. B. Gloyer, H. Aghajan, K.-Y. Siu, and T. Kailath, "Video-based freeway monitoring system using recursive vehicle tracking," in Proceedings of SPIE, 2421, pp. 173-180, Feb 1995.
16. B. Lo and S. Velastin, "Automatic congestion detection system for underground platforms," in Proceedings of 2001 International symposium on intelligent multimedia, video, and speech processing, pp. 158-161, (Hong Kong), May 2001.
17. Q. Zhou and J. Aggarwal, "Tracking and classifying moving objects from videos," in Proceedings of IEEE Workshop on Performance Evaluation of Tracking and Surveillance, 2001.
18. K. Toyama, J. Krumm, B. Brumitt, and B. Meyers, "Wallflower: Principles and practice of background maintenance," in ICCV (1), pp. 255-261, 1999.
19. N. McFarlane and C. Schofield, "Segmentation and tracking of piglets in images," Machine Vision and Applications 8(3), pp. 187-193, 1995.
20. P. Remagnino et al., "An integrated traffic and pedestrian model-based vision system," in Proceedings of the Eighth British Machine Vision Conference, pp. 380-389, 1997.
21. J. Heikkila and O. Silven, "A real-time system for monitoring of cyclists and pedestrians," in Second IEEE Workshop on Visual Surveillance, pp. 246-252, (Fort Collins, Colorado), Jun 1999.
22. G. Halevy and D. Weinshall, "Motion of disturbances: detection and tracking of multi-body non-rigid motion," Maching Vision and Applications 11, pp. 122-137, 1999.
23. T. Boult et al., "Frame-rate omnidirectional surveillance and tracking of camuflaged and occluded targets," in Proceedings Second IEEE Workshop on Visual Surveillance, pp. 48-55, (Fort Collins, CO), June 1999.
24. K.-P. Karmann and A. Brandt, "Moving object recognition using and adaptive background memory," in Time- Varying Image Processing and Moving Object Recognition, V. Cappellini, ed., 2, pp. 289-307, Elsevier Science Publishers B.V., 1990.
25. N. Friedman and S. Russell, "Image segmentation in video sequences: A probabilistic approach," in Proceedings of the Thirteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-97), pp. 175-181, Morgan Kaufmann Publishers, Inc., (San Francisco, CA), 1997.
26. P. W. Power and J. A. Schoonees, "Understanding background mixture models for foreground segmentation," in Proceedings Image and Vision Computing New Zealand, pp. 267-271, (Auckland, New Zealand), Nov 2002.
27. X. Gao, T. Boult, F. Coetzee, and V. Ramesh, "Error analysis of background adaption," in Proceedings IEEE conference on computer vision and pattern recognition, 1, pp. 503-510, (Hilton Head Isand, SC), June 2000.
28. D.-S. Lee, J. Hull, and B. Erol, "A Bayesian framework for gaussian mixture background modeling," in Proceedings of IEEE International Confererence on Image Processing, (Barcelona, Spain), Sept 2003.
29. L. Fuentes and S. Velastin, "From tracking to advanced surveillance," in Proceedings of IEEE International Confererence on Image Processing, (Barcelona, Spain), Sept 2003.
30. B. Horn, Robot Vision, The MIT Press, 1986.
31. D. Gutchess et al., "A background model initialization algorithm for video surveillance," in Proceedings Eighth IEEE International Conference on Computer Vision, 1, pp. 744-740, (Vancouver, BC), July 2001.
32. Y. Ivanov, A. Bobick, and J. Liu, "Fast lighting independent background," International Journal of Computer Vision 37(2), pp. 199-207, 2000.
33. A. Prati, I. Mikic, M. Trivedi, and R. Cucchiara, "Detecting moving shadows: algorithms and evaluation," IEEE Transactions on Pattern Analysis and Maching Intelligence 25, pp. 918-923, July 2003.
34. C. J. van Rijsbergen, Information retrieval, Butterworth & Co (Publishers) Ltd, second ed., 1979.