C. Kuo, C. Huang, and R. Nevatia, Multi-target tracking by online learned discriminative appearance models, the IEEE CVPR, 2010.

B. Leibe, K. Schindler, and L. Van-gool, Coupled Detection and Trajectory Estimation for Multi-Object Tracking, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408936

A. P. Leung and S. Gong, Mean-Shift Tracking with Random Sampling, Procedings of the British Machine Vision Conference 2006, 2006.
DOI : 10.5244/C.20.75

L. Snidaro, I. Visentini, and G. L. Foresti, Dynamic Models for People Detection and Tracking, 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance, pp.29-35, 2008.
DOI : 10.1109/AVSS.2008.29

A. Yilmaz, O. Javed, and M. Shah, Object tracking, ACM Computing Surveys, vol.38, issue.4, 2006.
DOI : 10.1145/1177352.1177355

M. D. Breitenstein, F. Reichlin, B. Leibe, E. Koller-meier, and L. V. , Robust tracking-by-detection using a detector confidence particle filter, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459278

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

B. Leibe, A. Leonardis, and B. Schiele, Robust Object Detection with Interleaved Categorization and Segmentation, International Journal of Computer Vision, vol.73, issue.2, pp.259-289, 2008.
DOI : 10.1007/s11263-007-0095-3

F. Moutarde, B. Stanciulescu, and A. Breheret, Real time visual detection of vehicles and pedestrians with new efficient adaboost features, IEEE International Conference on Intelligent Robots Systems, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00320888

B. Wu and R. Nevatia, Detection and Tracking of Multiple, Partially Occluded Humans by Bayesian Combination of Edgelet based Part Detectors, International Journal of Computer Vision, vol.I, issue.4, pp.247-266, 2007.
DOI : 10.1007/s11263-006-0027-7

N. T. Siebel and S. Maybank, Fusion of Multiple Tracking Algorithms for Robust People Tracking, Proc. ECCV, 373?387, 2002.
DOI : 10.1007/3-540-47979-1_25

D. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004.
DOI : 10.1023/B:VISI.0000029664.99615.94

Y. Ke and R. Sukthankar, PCA-SIFT: A More Distinctive Representation for Local Image Descriptors, Proc.CVPR, pp.506-513, 2004.

K. Mikolajczyk and C. Schmid, A performance evaluation of local descriptors, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.27, issue.10, pp.1615-1630, 2005.
DOI : 10.1109/TPAMI.2005.188

URL : https://hal.archives-ouvertes.fr/inria-00548227

E. Tola, V. Lepetit, and P. Fua, A fast local descriptor for dense matching, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587673

H. Bay, T. Tuytelaars, and L. V. , SURF: Speeded up robust features, 2006.
DOI : 10.1007/11744023_32

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

M. Calonder, V. Lepetit, C. Strecha, and P. Fua, BRIEF: Binary Robust Independent Elementary Features, 11th ECCV, 2010.
DOI : 10.1007/978-3-642-15561-1_56

N. Gordon, D. Salmond, and A. Smith, Novel approach to non-linear/non-Gaussian Bayesian state estimation, IEE Proceedings-F, vol.140, issue.2, pp.107-113, 1993.

M. Isard and A. Blake, Condensation?conditional density propagation for visual tracking, International Journal of Computer Vision, vol.29, issue.1, pp.5-28, 1998.
DOI : 10.1023/A:1008078328650

G. Kitagawa, Monte Carlo filter and smoother for non- Gaussian nonlinear state space models, Journal of Computational and Graphical Statistics, vol.5, issue.1, pp.1-25, 1996.

K. Okuma, A. Taleghani, N. De-freitas, J. Little, and D. Lowe, A Boosted Particle Filter: Multitarget Detection and Tracking, ECCV, 2004.
DOI : 10.1007/978-3-540-24670-1_3

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

J. Vermaak, A. Doucet, and P. Perez, Maintaining multimodality through mixture tracking, Proceedings Ninth IEEE International Conference on Computer Vision, 2003.
DOI : 10.1109/ICCV.2003.1238473

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

A. Almeida, J. Almeida, and R. Araujo, Real-time tracking of multiple moving objects using particle filters and probabilistic data association, Automatika, vol.46, issue.12, pp.39-48, 2005.

Y. Rui and Y. Chen, Better Proposal Distributions: Object Tracking Using Unscented Particle Filter, the IEEE CVPR, 2001.

K. Nummiaro, E. Koller-meier, and L. Van-gool, An adaptive color-based particle filter, Image and Vision Computing, vol.21, issue.1, pp.99-110, 2003.
DOI : 10.1016/S0262-8856(02)00129-4

D. B. Rubin, The calculation of posterior distributions by data augmentation, Jornal of the American Statistical Association, 1987.

A. F. Smith and A. E. Gelfand, Bayesian statistics without tears: A sampling?resampling perspective " . The American Statistician, pp.84-88, 1992.

H. W. Kuhn, The Hungarian method for the assignment problem, Naval Research Logistics Quarterly, vol.3, issue.1-2, pp.83-97
DOI : 10.1002/nav.3800020109

B. S. Manjunath, J. Ohm, V. V. Vasudevan, and A. Yamada, Color and texture descriptors, IEEE Transactions on Circuits and Systems for Video Technology, pp.703-715, 2001.
DOI : 10.1109/76.927424

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

D. P. Chau, F. Bremond, M. Thonnat, and E. Corvee, Robust mobile object tracking based on multiple feature similarity and trajectory filtering, The International Conference on Computer Vision Theory and Applications (VISAPP), 2011.
URL : https://hal.archives-ouvertes.fr/inria-00599734