A. Yilmaz, O. Javed, and M. Shah, Object tracking, ACM Computing Surveys, vol.38, issue.4, pp.1-45, 2006.
DOI : 10.1145/1177352.1177355

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

P. Pérez, C. Hue, J. Vermaak, and M. Gangnet, Color-Based Probabilistic Tracking, ECCV, pp.661-675, 2002.
DOI : 10.1007/3-540-47969-4_44

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

S. K. Zhou, R. Chellappa, and B. Moghaddam, Visual Tracking and Recognition Using Appearance-Adaptive Models in Particle Filters, IEEE Transactions on Image Processing, vol.13, issue.11, pp.1491-1506, 2004.
DOI : 10.1109/TIP.2004.836152

H. Wang, D. Suter, K. Schindler, and C. Shen, Adaptive Object Tracking Based on an Effective Appearance Filter, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.9, pp.1661-1667, 2007.
DOI : 10.1109/TPAMI.2007.1112

L. Jin, J. Cheng, and H. Huang, Human tracking in the complicated background by particle filter using color-histogram and hog, ISPCS, pp.1-4, 2010.

A. Yao, G. Wang, X. Lin, and X. Chai, An incremental Bhattacharyya dissimilarity measure for particle filtering, Pattern Recognition, vol.43, issue.4, pp.1244-1256, 2010.
DOI : 10.1016/j.patcog.2009.09.024

X. Li, W. Hu, Z. Zhang, X. Zhang, and G. Luo, Robust Visual Tracking Based on Incremental Tensor Subspace Learning, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408950

D. A. Ross, J. Lim, R. S. Lin, and M. H. Yang, Incremental Learning for Robust Visual Tracking, International Journal of Computer Vision, vol.61, issue.3, pp.125-141, 2008.
DOI : 10.1007/s11263-007-0075-7
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.139.4310

J. Kwon, K. M. Lee, and F. C. Park, Visual tracking via geometric particle filtering on the affine group with optimal importance functions, CVPR, pp.991-998, 2009.

W. R. Gilks and C. Berzuini, Following a moving target-Monte Carlo inference for dynamic Bayesian models, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.63, issue.1, pp.127-146, 2001.
DOI : 10.1111/1467-9868.00280

Z. Khan, T. Balch, and F. Dellaert, MCMC-based particle filtering for tracking a variable number of interacting targets, pp.1805-1918, 2005.

S. K. Pang, J. Li, and S. J. , Models and algorithms for detection and tracking of coordinated groups, IEEE Aerospace Conference, pp.1-17, 2008.

F. Septier, A. Carmi, and . Pang, Multiple object tracking using evolutionary and hybrid MCMC-based particle algorithms, 15th IFAC Symposium on System Identification, 2009.
DOI : 10.3182/20090706-3-fr-2004.00132
URL : https://hal-institut-mines-telecom.archives-ouvertes.fr/hal-00566628/document

F. Septier, S. K. Pang, A. Carmi, and S. Godsill, On MCMCbased particle methods for bayesian filtering: Application to multitarget tracking, 3rd IEEE, pp.360-363, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00566647

J. Vermaak, P. Lawrence, and . Perez, Variational inference for visual tracking, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., 2003.
DOI : 10.1109/CVPR.2003.1211431

Y. Rubner, J. Puzicha, C. Tomasi, and J. M. Buhmann, Empirical Evaluation of Dissimilarity Measures for Color and Texture, Computer Vision and Image Understanding, vol.84, issue.1, pp.25-43, 2001.
DOI : 10.1006/cviu.2001.0934

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), pp.886-893, 2005.
DOI : 10.1109/CVPR.2005.177
URL : https://hal.archives-ouvertes.fr/inria-00548512

M. D. Breitenstein, F. Reichlin, B. Leibe, E. Koller-meier, and L. Van-gool, Online multi-person tracking-by-detection from a single, uncalibrated camera, 2010.