P. F. Ash and E. D. Bolker, Generalized Dirichlet tessellations, Geometriae Dedicata, vol.1, issue.2, pp.209-243, 1986.
DOI : 10.1007/BF00164401

J. Besag, Statistical analysis of dirty pictures*, Journal of Applied Statistics, vol.6, issue.5-6, pp.259-302, 1986.
DOI : 10.1016/0031-3203(83)90012-2

Y. Boykov and V. Kolmogorov, An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.9, pp.1124-1137, 2004.
DOI : 10.1109/TPAMI.2004.60

Y. Boykov, O. Veksler, and R. Zabih, Fast approximate energy minimization via graph cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.11, pp.1222-1239, 2001.
DOI : 10.1109/34.969114

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.112.6806

P. B. Chou and C. M. Brown, The theory and practice of Bayesian image labeling, International Journal of Computer Vision, vol.83, issue.2, pp.185-210, 1990.
DOI : 10.1007/BF00054995

P. Danielsson, Euclidean distance mapping, Computer Graphics and Image Processing, vol.14, issue.3, pp.227-248, 1980.
DOI : 10.1016/0146-664X(80)90054-4

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.322.7605

P. Felzenszwalb and D. Huttenlocher, Efficient belief propagation for early vision, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., 2006.
DOI : 10.1109/CVPR.2004.1315041

S. Geman and D. Geman, Stochastic relaxation, gibbs distributions , and the bayesian restoration of images, IEEE T- PAMI, vol.6, issue.6 1, pp.721-741, 1984.

B. Glocker, A. Sotiras, N. Komodakis, and N. Paragios, Deformable Medical Image Registration: Setting the State of the Art with Discrete Methods, Annual Review of Biomedical Engineering, vol.13, issue.1, pp.219-263, 2011.
DOI : 10.1146/annurev-bioeng-071910-124649

URL : https://hal.archives-ouvertes.fr/hal-00858380

D. M. Greig, B. T. Porteous, and A. J. Seheult, Exact minimum a posteriori estimation for binary images, Journal of the Royal Society. Series B (Methodological), vol.51, issue.2 1, pp.271-279, 1989.

V. Kolmogorov, Convergent Tree-Reweighted Message Passing for Energy Minimization, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.10, pp.1568-1583, 2005.
DOI : 10.1109/TPAMI.2006.200

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.100.2409

V. Kolmogorov and R. Zabih, What energy functions can be minimized via graph cuts, IEEE T-PAMI, vol.26, issue.1, pp.65-81, 2004.
DOI : 10.1109/tpami.2004.1262177

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.113.1823

N. Komodakis, N. Paragios, and G. Tziritas, MRF Optimization via Dual Decomposition: Message-Passing Revisited, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408890

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.3345

N. Komodakis, G. Tziritas, and N. Paragios, Fast, Approximately Optimal Solutions for Single and Dynamic MRFs. Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, issue.1, 2007.

X. Lan, S. Roth, D. Huttenlocher, and M. J. Black, Efficient Belief Propagation with Learned Higher-Order Markov Random Fields, ECCV, p.7, 2006.
DOI : 10.1109/TIP.2003.819861

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.70.8126

K. P. Murphy, Y. Weiss, and M. I. Jordan, Loopy belief propagation for approximate inference: An empirical study, Proceedings of Uncertainty in AI, 1999.

. Nvidia, Nvidia cuda programming guide, 2011.

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

G. Rong and T. Tan, Jump flooding in GPU with applications to Voronoi diagram and distance transform, Proceedings of the 2006 symposium on Interactive 3D graphics and games , SI3D '06, pp.109-116, 2006.
DOI : 10.1145/1111411.1111431

S. Roth and M. Black, Fields of Experts: A Framework for Learning Image Priors, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
DOI : 10.1109/CVPR.2005.160

C. Rother, V. Kolmogorov, and A. Blake, "GrabCut", ACM Transactions on Graphics, vol.23, issue.3, pp.309-314, 2004.
DOI : 10.1145/1015706.1015720

M. F. Tappen and W. T. Freeman, Comparison of graph cuts with belief propagation for stereo, using identical MRF parameters, Proceedings Ninth IEEE International Conference on Computer Vision, p.900, 2003.
DOI : 10.1109/ICCV.2003.1238444

Y. W. Teh, S. Osindero, and G. E. Hinton, Energy-based models for sparse overcomplete representations, JMLR, vol.4, issue.6, pp.1235-1260, 2004.

M. J. Wainwright, T. S. Jaakkola, and A. S. Willsky, Treebased reparameterization framework for analysis of sumproduct and related algorithms. Information Theory, IEEE Transactions on, vol.49, issue.5, pp.1120-1146, 2002.

Y. Xu, H. Chen, R. Klette, J. Liu, and T. Vaudrey, Belief Propagation Implementation Using CUDA on an NVIDIA GTX 280, Advances in Artificial Intelligence, 2009.
DOI : 10.1007/978-3-642-10439-8_19