E. Besada-portas, S. M. Plis, J. M. Cruz, and T. Lane, Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks, ECML PKDD, pp.131-146, 2009.
DOI : 10.1002/1097-0193(200007)10:3<120::AID-HBM30>3.0.CO;2-8

M. Bray, E. Koller-meier, P. Müller, N. N. Schraudolph, and L. Van-gool, Stochastic optimization for high-dimensional tracking in dense range maps, IEE Proceedings Vision, Image and Signal Processing, pp.501-512, 2005.

S. Derrode and W. Pieczynski, Signal and Image Segmentation Using Pairwise Markov Chains, IEEE Transactions on Signal Processing, vol.52, issue.9, pp.2477-2489, 2004.
DOI : 10.1109/TSP.2004.832015
URL : https://hal.archives-ouvertes.fr/hal-01346595

J. Deutscher and I. Reid, Articulated Body Motion Capture by Stochastic Search, International Journal of Computer Vision, vol.61, issue.2, pp.185-205, 2005.
DOI : 10.1023/B:VISI.0000043757.18370.9c

A. Doucet, N. De-freitas, K. Murphy, and S. Russell, Rao- Blackwellised particle filtering for dynamic Bayesian networks, UAI, pp.176-183, 2000.

C. Gonzales, S. Dubuisson, and X. Nguyen, Simultaneous Partitioned Sampling for Articulated Object Tracking, ACIVS, Lecture Notes in Computer Science, pp.150-161, 2011.
DOI : 10.1007/978-3-642-23687-7_14
URL : https://hal.archives-ouvertes.fr/hal-01285664

N. J. Gordon, D. J. Salmond, and A. F. Smith, Novel approach to nonlinear/non-Gaussian Bayesian state estimation, IEE Proceedings F Radar and Signal Processing, vol.140, issue.2, pp.107-113, 1993.
DOI : 10.1049/ip-f-2.1993.0015

K. Kanazawa, D. Koller, and S. Russell, Stochastic simulation algorithms for dynamic probabilistic networks, UAI, pp.346-381, 1995.

J. Maccormick and A. Blake, A probabilistic exclusion principle for tracking multiple objects, Proceedings of the Seventh IEEE International Conference on Computer Vision, pp.572-587, 1999.
DOI : 10.1109/ICCV.1999.791275

J. Maccormick and M. Isard, Partitioned Sampling, Articulated Objects, and Interface-Quality Hand Tracking, ECCV, pp.3-19, 2000.
DOI : 10.1007/3-540-45053-X_1

K. Murphy, Dynamic Bayesian Networks : Representation, Inference and Learning, 2002.

J. Pearl, Probabilistic Reasoning in Intelligent Systems : Networks of Plausible Inference, 1988.

C. Rose, J. Saboune, and F. Charpillet, Reducing particle filtering complexity for 3D motion capture using dynamic Bayesian networks, pp.1396-1401, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00332714

A. Sánchez, J. Pantrigo, and K. Gianikellis, Combining Particle Filter and Population-based Metaheuristics for Visual Articulated Motion Tracking, Electronic Letters on Computer Vision and Image Analysis, vol.5, issue.3, pp.68-83, 2005.

E. B. Sudderth, A. T. Ihler, M. Isard, W. T. Freeman, and A. S. Willsky, Nonparametric belief propagation, Communications of the ACM, vol.53, issue.10, pp.95-103, 2010.
DOI : 10.1145/1831407.1831431
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.9687