P. Kohli, M. P. Kumar, and P. H. Torr, P³ & Beyond: Move Making Algorithms for Solving Higher Order Functions, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.9, pp.1645-1656, 2009.
DOI : 10.1109/TPAMI.2008.217

N. Komodakis, G. Tziritas, and N. Paragios, Fast, Approximately Optimal Solutions for Single and Dynamic MRFs, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383095

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

V. Kolmogorov and R. Zabih, Multi-camera Scene Reconstruction via Graph Cuts, Proc. European Conf. Computer Vision, pp.82-96, 2002.
DOI : 10.1007/3-540-47977-5_6

C. Rother, S. Kumar, V. Kolmogorov, and A. Blake, Digital Tapestry, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.589-596, 2005.
DOI : 10.1109/CVPR.2005.130

R. Szeliski, R. Zabih, D. Scharstein, O. Veksler, V. Kolmogorov et al., A Comparative Study of Energy Minimization Methods for Markov Random Fields, Proc. European Conf. Computer Vision, pp.16-29, 2006.
DOI : 10.1007/3-540-47977-5_58

J. S. Yedidia, W. T. Freeman, and Y. Weiss, Generalized belief propagation, NIPS, pp.689-695, 2000.

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

D. Freedman and P. Drineas, Energy Minimization via Graph Cuts: Settling What is Possible, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.939-946, 2005.
DOI : 10.1109/CVPR.2005.143

H. Ishikawa, Exact optimization for markov random fields with convex priors, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.10, pp.1333-1336, 2003.
DOI : 10.1109/TPAMI.2003.1233908

V. Kolmogorov and R. Zabih, What energy functions can be minimized via graph cuts?, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.2, pp.147-159, 2004.
DOI : 10.1109/TPAMI.2004.1262177

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, 2006.
DOI : 10.1109/TPAMI.2006.200

M. J. Wainwright, T. Jaakkola, and A. S. Willsky, MAP Estimation Via Agreement on Trees: Message-Passing and Linear Programming, IEEE Transactions on Information Theory, vol.51, issue.11, pp.3697-3717, 2005.
DOI : 10.1109/TIT.2005.856938

P. F. Felzenszwalb and D. P. Huttenlocher, Efficient belief propagation for early vision, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., pp.261-268, 2004.
DOI : 10.1109/CVPR.2004.1315041

O. Juan and Y. Boykov, Active Graph Cuts, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1 (CVPR'06), pp.1023-1029, 2006.
DOI : 10.1109/CVPR.2006.47

P. Kohli and P. H. Torr, Effciently solving dynamic Markov random fields using graph cuts, Proc. Int'l Conf. Computer Vision, pp.922-929, 2005.

N. Komodakis and G. Tziritas, A new framework for approximate labeling via graph cuts, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.1018-1025, 2005.
DOI : 10.1109/ICCV.2005.14

V. Kolmogorov and C. Rother, Minimizing non-submodular functions with graph cuts: a review, IEEE Trans. Pattern Anal. Mach. Intell, vol.29, issue.2, 2007.

I. Kovtun, Partial Optimal Labeling Search for a NP-Hard Subclass of (max,+) Problems, DAGM Symposium, pp.402-409, 2003.
DOI : 10.1007/978-3-540-45243-0_52

E. Boros and P. L. Hammer, Pseudo-Boolean optimization, Discrete Applied Mathematics, vol.123, issue.1-3, pp.155-225, 2002.
DOI : 10.1016/S0166-218X(01)00341-9
URL : https://hal.archives-ouvertes.fr/hal-01150533

Y. Boykov and M. Jolly, Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, pp.105-112, 2001.
DOI : 10.1109/ICCV.2001.937505

J. Shotton, J. M. Winn, C. Rother, and A. Criminisi, TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation, Proc. European Conf. Computer Vision, pp.1-15, 2006.
DOI : 10.1007/11744023_1

R. Paget and I. D. Longstaff, Texture synthesis via a noncausal nonparametric multiscale Markov random field, IEEE Transactions on Image Processing, vol.7, issue.6, pp.925-931, 1998.
DOI : 10.1109/83.679446

S. Roth and M. J. Black, Fields of Experts: A Framework for Learning Image Priors, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.860-867, 2005.
DOI : 10.1109/CVPR.2005.160

X. Lan, S. Roth, D. P. Huttenlocher, and M. J. Black, Efficient Belief Propagation with Learned Higher-Order Markov Random Fields, Proc. European Conf. Computer Vision, pp.269-282, 2006.
DOI : 10.1109/TIP.2003.819861

P. Kohli, L. Ladicky, and P. H. Torr, Graph cuts for minimizing robust higher order potentials, Proc. Int'l Conf. Computer Vision and Pattern Recognition, 2008.

S. Iwata, S. T. Mccormick, and M. Shigeno, A Strongly Polynomial Cut Canceling Algorithm for the Submodular Flow Problem, ICPO, pp.259-272, 1999.
DOI : 10.1007/3-540-48777-8_20

B. A. Zalesky, Efficient determination of Gibbs estimators with submodular energy functions, 2003.

D. Schlesinger and B. Flach, Transforming an arbitrary minsum problem into a binary one, 2006.

J. Pearl, Probabilistic reasoning in intelligent systems: Networks of plausible inference, 1998.

M. I. Schlesinger and V. Hlavac, Ten Lectures on Statistical and Structural Pattern Recognition, 2002.
DOI : 10.1007/978-94-017-3217-8

T. Werner, A Linear Programming Approach to Max-Sum Problem: A Review, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.7, pp.1165-1179, 2007.
DOI : 10.1109/TPAMI.2007.1036

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

P. Kohli, A. Shekhovtsov, C. Rother, V. Kolmogorov, and P. H. Torr, On partial optimality in multi-label MRFs, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.480-487, 2008.
DOI : 10.1145/1390156.1390217

I. Kovtun, Image segmentation based on sufficient conditions for optimality in NP-complete classes of structural labeling problems, IRTC ITS Nat. Academy of Science Ukraine, 2004.

D. Scharstein and R. Szeliski, A taxonomy and evaluation of dense two-frame stereo correspondence algorithms, Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001), pp.7-42, 2002.
DOI : 10.1109/SMBV.2001.988771

F. Schroff, A. Criminisi, and A. Zisserman, Single-Histogram Class Models for Image Segmentation, ICVGIP, 2006.
DOI : 10.1007/11949619_8
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.329.4792

S. Birchfield and C. Tomasi, A pixel dissimilarity measure that is insensitive to image sampling, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.4, pp.401-406, 1998.
DOI : 10.1109/34.677269