M. Kass, A. Witkin, and D. Terzopoulos, Snakes: Active contour models, International Journal of Computer Vision, vol.5, issue.6035, pp.321-331, 1988.
DOI : 10.1007/BF00133570
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.124.5318

V. Caselles, R. Kimmel, and G. Sapiro, Geodesic active contours, Proceedings of IEEE International Conference on Computer Vision, pp.61-79, 1997.
DOI : 10.1109/ICCV.1995.466871
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.21.2196

S. Osher and J. A. Sethian, Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations, Journal of Computational Physics, vol.79, issue.1, pp.12-49, 1988.
DOI : 10.1016/0021-9991(88)90002-2

T. F. Chan and L. A. Vese, Active contours without edges, IEEE Transactions on Image Processing, vol.10, issue.2, pp.266-277, 2001.
DOI : 10.1109/83.902291
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.1828

Y. Boykov and M. P. 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

E. Bae, J. Yuan, and X. Tai, Global Minimization for Continuous Multiphase Partitioning Problems Using a Dual Approach, International Journal of Computer Vision, vol.51, issue.11, pp.112-129, 2011.
DOI : 10.1007/s11263-010-0406-y

M. Nikolova, S. Esedoglu, and T. F. Chan, Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models, SIAM JAM, vol.66, issue.5, pp.1632-1648, 2006.

T. Pock, T. Schoenemann, G. Graber, H. Bischof, and D. Cremers, A Convex Formulation of Continuous Multi-label Problems, ECCV, pp.792-805, 2008.
DOI : 10.1007/978-3-540-88690-7_59

T. Pock, D. Cremers, H. Bischof, and A. Chambolle, Global Solutions of Variational Models with Convex Regularization, SIAM Journal on Imaging Sciences, vol.3, issue.4, pp.1122-1145, 2010.
DOI : 10.1137/090757617

E. Brown, T. F. Chan, and X. Bresson, Completely Convex Formulation of the Chan-Vese Image Segmentation Model, International Journal of Computer Vision, vol.26, issue.2, pp.1-19, 2011.
DOI : 10.1007/s11263-011-0499-y

T. F. Chan, G. H. Golub, and P. Mulet, A nonlinear primal-dual method for total variation-based image restoration, SIAM JSC, vol.20, pp.1964-1977, 1999.

A. Chambolle and T. Pock, A First-Order Primal-Dual Algorithm for Convex Problems with??Applications to Imaging, Journal of Mathematical Imaging and Vision, vol.60, issue.5, pp.120-145, 2011.
DOI : 10.1007/s10851-010-0251-1
URL : https://hal.archives-ouvertes.fr/hal-00490826

R. T. Rockafellar, Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming, Mathematics of Operations Research, vol.1, issue.2, pp.97-116, 1976.
DOI : 10.1287/moor.1.2.97

M. Zhu and T. Chan, An efficient primal-dual hybrid gradient algorithm for total variation image restauration, 2008.

A. Baeza, V. Caselles, P. Gargallo, and N. Papadakis, A Narrow Band Method for the Convex Formulation of Discrete Multilabel Problems, Multiscale Modeling & Simulation, vol.8, issue.5, pp.2048-2078, 2010.
DOI : 10.1137/090780936
URL : https://hal.archives-ouvertes.fr/hal-00596060