W. Hu, T. N. Tan, L. Wang, and S. J. Maybank, A Survey on Visual Surveillance of Object Motion and Behaviors, IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), vol.34, issue.3, 2004.
DOI : 10.1109/TSMCC.2004.829274

Y. Zhang and Q. Ji, Active and dynamic information fusion for facial expression understanding from image sequences, IEEE Trans. on PAMI, vol.27, issue.5, p.699714, 2005.

A. Efros, A. Berg, G. Mori, and J. Malik, Recognizing action at a distance, Proceedings Ninth IEEE International Conference on Computer Vision, p.726733, 2003.
DOI : 10.1109/ICCV.2003.1238420

N. Robertson and I. Reid, Behaviour understanding in video: a combined method, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005.
DOI : 10.1109/ICCV.2005.47

T. Jebara, Y. Song, and K. Thadani, Spectral Clustering and Embedding with Hidden Markov Models, Lecture Notes in Computer Science, vol.4701, p.164175, 2007.
DOI : 10.1007/978-3-540-74958-5_18

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

T. W. Liao, Clustering of time series data: A survey, Pattern Recognition, vol.38, issue.11, 2005.

J. Niebles and L. F. Wang, Unsupervised learning of human action categories using spatial-temporal words, Proc. of BMVC, 2006.

D. Makris and T. Ellis, Learning Semantic Scene Models From Observing Activity in Visual Surveillance, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.35, issue.3, 2005.
DOI : 10.1109/TSMCB.2005.846652

N. Johnson and D. Hogg, Learning the distribution of object trajectories for event recognition, Image and Vision Computing, vol.14, issue.8, 1996.
DOI : 10.1016/0262-8856(96)01101-8

M. Pittore, M. Campani, and A. Verri, Learning to recognize visual dynamic events from examples, IJCV, 2000.

W. Lin, M. A. Orgun, and G. J. Williams, Temporal data mining using multilevellocal polynominal models, Int. Conf. IDEAL, 1983.

L. R. Rabiner, A tutorial on hidden Markov models and selected applications in speech recognition, Proceedings of the IEEE, vol.77, p.257286, 1989.

O. Chung, Spectral graph theory (reprinted with corrections), CBMS: Conference Board of the Mathematical Sciences, Regional Conference Series, 1997.

A. Ng, M. Jordan, and Y. Weiss, On spectral clustering: Analysis and an algorithm, p.14, 2002.

J. Shi and J. Malik, Normalized cuts and image segmentation, IEEE Trans. on PAMI, vol.22, issue.8, p.888905, 2000.

J. S. Taylor and N. Cristianini, Kernel Methods for Pattern Analysis, 2004.

T. Jebara, R. I. Kondor, and A. Howard, Probability product kernels, Journal of Machine Learning Research, vol.5, p.819844, 2004.

C. Leslie, E. Eskin, and W. Noble, THE SPECTRUM KERNEL: A STRING KERNEL FOR SVM PROTEIN CLASSIFICATION, Biocomputing 2002, 2003.
DOI : 10.1142/9789812799623_0053

F. Camastra and A. Verri, A novel kernel method for clustering, IEEE Trans. on PAMI, vol.27, issue.5, p.801804, 2005.