Robust visual behavior recognition

IEEE Signal Processing Magazine

Volumn 27, Issue 5, 2010, Pages 34-45

  Kosmopoulos, Dimitrios ^a,b   Chatzis, Sotirios P ^c  

^a INSTITUTE OF INFORMATICS AND TELECOMMUNICATIONS   (Greece)

^b NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^c IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRICAL ENGINEERING; SIGNAL PROCESSING;

MODEL ALGORITHMS; MODEL TRAINING; MULTIPLE CAMERAS; MULTIPLE SOURCE; REAL-TIME ACTIVITY RECOGNITION; SEMI- SUPERVISED LEARNING; SEQUENTIAL DATA; VISUAL BEHAVIOR;

BEHAVIORAL RESEARCH;

EID: 85032751271     PISSN: 10535888     EISSN: None     Source Type: Journal    
DOI: 10.1109/MSP.2010.937392     Document Type: Article

References (21)

1. W. Hu, T. Tan, L. Wang, and S. Maybank, "A survey on visual surveillance of object motion and behaviors," IEEE Trans. Systems, Man, Cybern. C, vol.34, no.3, pp. 334-352, 2004.
2. C. Stauffer, W. Eric, and W. E. L. Grimson, "Learning patterns of activity using real-time tracking," IEEE Trans. Pattern Anal. Machine Intell., vol.22, no.8, pp. 747-757, 2000.
3. X. Sun, M. Chen, and A. Hauptmann, "Action recognition via local descriptors and holistic features," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2009, pp. 58-65.
4. G. Willems, T. Tuytelaars, and L. Gool, "An efficient dense and scale-invariant spatio-temporal interest point detector," in Proc. 10th European Conf. Computer Vision. Berlin: Springer-Verlag, 2008, pp. 650-663.
5. E. Shechtman and M. Irani, "Space-time behavior-based correlation\or\how to tell if two underlying motion fields are similar without computing them?" IEEE Trans. Pattern Anal. Machine Intell., vol.29, no.11, pp. 2045-2056, 2007.
6. J. W. Davis and A. F. Bobick, "The representation and recognition of action using temporal templates," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1997, pp. 928-934.
7. T. Xiang and S. Gong, "Beyond tracking: Modelling activity and understanding behaviour," Int. J. Comput. Vis., vol.67, no.1, pp. 21-51, 2006.
8. J. Flusser, B. Zitova, and T. Suk, Moment Functions in Image Analysis: Theory and Applications. Hoboken, NJ: Wiley, 2009.
9. G. J. McLachlan, Discriminant Analysis and Statistical Pattern Recognition. Hoboken, NJ: Wiley, 2004.
10. L. R. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," Proc. IEEE, vol.77, no.2, pp. 257-286, 1989.
11. C. Li and G. Biswas, "Temporal pattern generation using hidden Markov model based unsupervised classification," in Advances in Intelligent Data Analysis (Proc. 3rd Int. Symp., IDA-99, Amsterdam, The Netherlands, Aug. 1999) (Lecture Notes in Computer Science, vol. 1642). New York: Springer-Verlag, 1999, pp. 245-256.
12. M. Ostendorf and H. Singer, "HMM topology design using maximum likelihood successive state splitting," Comput. Speech Lang., vol.11, no.1, pp. 17-41, 1997.
13. S. P. Chatzis, D. I. Kosmopoulos, and T. A. Varvarigou, "Robust sequential data modeling using an outlier tolerant hidden Markov model," IEEE Trans. Pattern Anal. Machine Intell., vol.31, no.9, pp. 1657-1669, 2009.
14. S. Ji, L. T. Watson, and L. Carin, "Semisupervised learning of hidden Markov models via a homotopy method," IEEE Trans. Pattern Anal. Machine Intell., vol.31, no.2, pp. 275-287, 2009.
15. S. Dupont and J. Luettin, "Audio-visual speech modeling for continuous speech recognition," IEEE Trans. Multimedia, vol.2, no.3, pp. 141-151, Sept. 2000.
16. C. Chenand, J. Liang, H. Zhao, H. Hu, and J. Tian, "Factorial HMM and parallel HMM for gait recognition," IEEE Trans. Systems, Man, Cybern. C, vol.39, no.1, pp. 114-123, 2009.
17. J. Luettin, G. Potamianos, and C. Neti, "Asynchronous stream modeling for large vocabulary audio-visual speech recognition," in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, 2001, pp. 169-172.
18. A. Nefian, L. Liang, X. Pi, L. Xiaoxiang, C. Mao, and K. Murphy, "A coupled HMM for audio-visual speech recognition," in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, 2002, vol.2, pp. 2013-2016.
19. Z. Zeng, J. Tu, B. Pianfetti, and T. Huang, "Audio-visual affective expression recognition through multistream fused HMM," IEEE Trans. Multimedia, vol.10, no.4, pp. 570-577, June 2008.
20. A. Makris, D. Kosmopoulos, S. Perantonis, and S. Theodoridis, "Hierarchical feature fusion for visual tracking," in Proc. IEEE Int. Conf. Image Processing, 2007, pp. VI:289-292.
21. N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2005, pp. 886-893