S. Rajasegarar, C. Leckie, and M. Palaniswami, Hyperspherical cluster based distributed anomaly detection in wireless sensor networks, Journal of Parallel and Distributed Computing, vol.74, issue.1, pp.1833-1847, 2014.
DOI : 10.1016/j.jpdc.2013.09.005

C. Stauffer and W. E. Grimson, Learning patterns of activity using real-time tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.22, issue.8, pp.747-757, 2000.
DOI : 10.1109/34.868677

J. Kim and K. Grauman, Observe locally, infer globally: a space-time MRF for detecting abnormal activities with incremental updates, IEEE Conference on Computer Vision and Pattern Recognition, pp.2921-2928, 2009.

R. Mehran, A. Oyama, and M. Shah, Abnormal crowd behavior detection using social force model, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.935-942, 2009.
DOI : 10.1109/CVPR.2009.5206641

D. Helbing and P. Molnar, Social force model for pedestrian dynamics, Physical Review E, vol.206, issue.5, p.4282, 1995.
DOI : 10.1016/0378-4371(94)90312-3

E. L. Andrade, S. Blunsden, and R. B. Fisher, Modelling Crowd Scenes for Event Detection, 18th International Conference on Pattern Recognition (ICPR'06), pp.175-178, 2006.
DOI : 10.1109/ICPR.2006.806

S. Rajasegarar, C. Leckie, and M. Palaniswami, Anomaly detection in wireless sensor networks, IEEE Wireless Communications, vol.15, issue.4, pp.34-40, 2008.
DOI : 10.1109/MWC.2008.4599219

V. Chandola, A. Banerjee, and V. Kumar, Anomaly detection, ACM Computing Surveys, vol.41, issue.3, p.15, 2009.
DOI : 10.1145/1541880.1541882

S. Rajasegarar, C. Leckie, M. Palaniswami, and J. C. Bezdek, Quarter Sphere Based Distributed Anomaly Detection in Wireless Sensor Networks, 2007 IEEE International Conference on Communications, pp.3864-3869, 2007.
DOI : 10.1109/ICC.2007.637

O. Barnich and M. Van-droogenbroeck, ViBE: A powerful random technique to estimate the background in video sequences, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.945-948, 2009.
DOI : 10.1109/ICASSP.2009.4959741

E. V. Cuevas, D. Zaldivar, and R. Rojas, Kalman filter for vision tracking, 2005.

H. W. Kuhn, The Hungarian method for the assignment problem, Naval Research Logistics Quarterly, vol.3, issue.1-2, pp.83-97, 1955.
DOI : 10.2140/pjm.1953.3.369

A. S. Rao, J. Gubbi, S. Rajasegarar, S. Marusic, and M. Palaniswami, Detection of Anomalous Crowd Behaviour Using Hyperspherical Clustering, 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA), pp.1-8, 2014.
DOI : 10.1109/DICTA.2014.7008100

S. Ramaswamy, R. Rastogi, and K. Shim, Efficient algorithms for mining outliers from large data sets, ACM SIGMOD Record, pp.427-438, 2000.