S. Calderara, R. Cucchiara, and A. Prati, Detection of abnormal behaviors using a mixture of Von Mises distributions, 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, 2007.
DOI : 10.1109/AVSS.2007.4425300

N. Anjum and A. Cavallaro, Multi-feature object trajectory clustering for video analysis, IEEE Transactions on Circuits for Video Technology, pp.1555-1564, 2008.

G. L. Foresti, C. Piciarelli, and C. Micheloni, Trajectorybased anomalous event detection, IEEE Transactions on Circuits and Systems for Video Technology, pp.1544-1554, 2008.

R. Hamid, S. Maddi, A. Johnson, A. Bobick, I. Essa et al., A novel sequence representation for unsupervised analysis of human activities , artificial intelligence journal, 2008.

T. Brendan, M. M. Morris, and . Trivedi, Learning and classification of trajectories in dynamic scenes: A general framework for live video analysis Advanced Video and Signal Based Surveillance, 2008.

W. Hu, X. Xiao, Z. Fu, and D. Xie, A system for learning statistical motion patterns, IEEE Trans. Pattern Anal. Mach. Intell, vol.28, issue.9, pp.1450-1464, 2006.

X. Li, W. Hu, and W. Hu, A coarse-to-fine strategy for vehicle motion trajectory clustering, ICPR '06: Proceedings of the 18th International Conference on Pattern Recognition, pp.591-594, 2006.

A. Hilton-thomas, B. Moeslund, and V. Kruger, A survey of advances in vision-based human motion capture and analysis, Comput. Vis. Image Underst, vol.104, issue.2, pp.90-126, 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, pp.397-408, 2005.
DOI : 10.1109/TSMCB.2005.846652

S. Sharat and . Chikkerur, Online fingerprint verification system -m.s. thesis http, 2005.

S. Khalid and A. Naftel, Classifying spatiotemporal object trajectories using unsupervised learning of basis function coefficients, Proceedings of the third ACM international workshop on Video surveillance & sensor networks , VSSN '05, 2005.
DOI : 10.1145/1099396.1099404

F. Porikli, Learning object trajectory patterns by spectral clustering. Multimedia and Expo, IEEE International Conference on, pp.1171-1174, 2004.
DOI : 10.1109/icme.2004.1394427

G. Antonini and J. Thiran, Trajectories clustering in ICA space: an application to automatic counting of pedestrians in video sequences, Advanced Concepts for Intelligent Vision Systems Proc. Intl. Soc. Mag. Reson. Med. IEEE, 2004.

S. G. Gong and T. Xiang, Recognition of group activities using dynamic probabilistic networks, ICCV03, pp.742-749, 2003.

I. Laptev and T. Lindeberg, Space-time interest points, ICCV, pp.432-439, 2003.
DOI : 10.1109/iccv.2003.1238378

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

N. M. Oliver, B. Rosario, and A. P. Pentland, A bayesian computer vision system for modeling human interactions. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.22, issue.8, pp.831-843, 2000.

I. Haritaoglu, D. Harwood, and L. S. Davis, W/sup 4/: real-time surveillance of people and their activities, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.22, issue.8, pp.809-830, 2000.
DOI : 10.1109/34.868683

J. Owens and A. Hunter, Application of the selforganizing map to trajectory classification, VS '00: Proceedings of the Third IEEE International Workshop on Visual Surveillance, 2000.

F. Aaron, A. D. Bobick, and . Wilson, A statebased approach to the representation and recognition of gesture, IEEE Trans. Pattern Anal. Mach. Intell, vol.19, issue.12, pp.1325-1337, 1997.