. Zonesec, , 2014.

D. Lambert, A blueprint for higher-level fusion systems, Information Fusion, vol.10, issue.1, pp.6-24, 2009.
DOI : 10.1016/j.inffus.2008.05.007

Z. Sabeur, Structured Multi-level Data Fusion and Modelling of Heterogeneous EnvironmentalData for Future Internet Applications, Geophysical Research Abstracts EGU General Assembly, vol.15, 2013.

Z. Zlatev, G. Veres, and Z. Sabeur, Agile Data Fusion and Knowledge Base Architecture for Critical Decision Support, International Journal of Decision Support System Technology, vol.5, issue.2, 2013.
DOI : 10.4018/jdsst.2013040101

V. Barat, D. Grishin, and M. Rostovtsev, Detection of AE signals against background fric tion, J.Acoust. Emission, vol.29, pp.133-141, 2011.

A. Yousefi and A. D. , Application of non-homogeneous HMM on detecting security fence breaching, Proceedings of the ICASSP, 2010.

N. Meinshausen, Quantile Regression Forests, Journal of Machine Learning Research, vol.7, pp.983-999, 2006.

A. Adam, E. Rivlin, I. Shimshoni, and D. Reinitz, Robust Real-Time Unusual Event Detection using Multiple Fixed-Location Monitors, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.3, pp.555-560, 2008.
DOI : 10.1109/TPAMI.2007.70825

M. D. Breitenstein, H. Grabner, and L. Van-gool, Hunting Nessie - Real-time abnormality detection from webcams, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, 2009.
DOI : 10.1109/ICCVW.2009.5457468

V. Saligrama and Z. Chen, Video anomaly detection based on local statistical aggregates, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012.
DOI : 10.1109/CVPR.2012.6247917

K. Yun, J. Kim, S. W. Kim, H. Jeong, and J. Y. Choi, Learning with Adaptive Rate for Online Detection of Unusual Appearance, Advances in Visual Computing, pp.698-707, 2014.
DOI : 10.1007/978-3-319-14249-4_67

M. Shah, O. Javed, and K. Shafique, Automated Visual Surveillance in Realistic Scenarios, IEEE Multimedia, vol.14, issue.1, pp.30-39, 2007.
DOI : 10.1109/MMUL.2007.3

N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
DOI : 10.1109/CVPR.2005.177
URL : https://hal.archives-ouvertes.fr/inria-00548512

I. Bouchrika, J. N. Carter, M. S. Nixon, R. Morzinger, and G. Thallinger, Using Gait Features for ImprovingWalking People Detection, International Conference on Pattern Recognition, 2010.
DOI : 10.1109/icpr.2010.758

J. C. Niebles, B. Han, and L. Fei-fei, Efficient extraction of human motion volumes by tracking, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5540152

J. M. Chaquet, E. J. Carmona, and A. Fernández-caballero, A survey of video datasets for human action and activity recognition, Computer Vision and Image Understanding, vol.117, issue.6, pp.633-659, 2013.
DOI : 10.1016/j.cviu.2013.01.013

S. Joo and Q. Zheng, A temporal variance-based moving target detector, IEEE Int, 2005.