D. Marr and T. Poggio, Cooperative computational of stereo disparity, Science, vol.194, pp.209-236, 1976.

A. Fusiello, V. Roberto, and E. Trucco, SYMMETRIC STEREO WITH MULTIPLE WINDOWING, International Journal of Pattern Recognition and Artificial Intelligence, vol.14, issue.08, pp.1053-1066, 2000.
DOI : 10.1142/S0218001400000696

C. L. Zitnick and T. Kanade, A cooperative algorithm for stereo matching and occlusion detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.22, issue.7, pp.675-684, 2000.
DOI : 10.1109/34.865184

M. Agrawal and L. Davis, Window-based, discontinuity preserving stereo, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., 2004.
DOI : 10.1109/CVPR.2004.1315015
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.6896

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

G. Aubert, R. Deriche, and P. Kornprobst, Computing Optical Flow via Variational Techniques, SIAM Journal on Applied Mathematics, vol.60, issue.1, pp.156-182, 1999.
DOI : 10.1137/S0036139998340170
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.736

L. Alvarez, R. Deriche, J. Sanchez, and J. Weickert, Dense Disparity Map Estimation Respecting Image Discontinuities: A PDE and Scale-Space Based Approach, Journal of Visual Communication and Image Representation, vol.13, issue.1-2, pp.3-21, 2002.
DOI : 10.1006/jvci.2001.0482
URL : https://hal.archives-ouvertes.fr/inria-00072780

N. Slesareva, A. Bruhn, and J. Weickert, Optic Flow Goes Stereo: A Variational Method for Estimating Discontinuity-Preserving Dense Disparity Maps, Pattern Recognition, pp.33-40, 2005.
DOI : 10.1007/11550518_5

P. Y. Simard and G. E. Mailloux, Vector field restoration by the method of convex projections, Computer Vision, Graphics, and Image Processing, 2000.

P. L. Combettes, The convex feasibiliy problem in image recovery Advances in Imaging and Electron Physics, pp.155-270, 1996.

L. I. Rudin, S. Osher, and E. Fatemi, Nonlinear total variation based noise removal algorithms, Physica D: Nonlinear Phenomena, vol.60, issue.1-4, pp.259-268, 1992.
DOI : 10.1016/0167-2789(92)90242-F

]. A. Fusiello, E. Trucco, and A. Verri, A compact algorithm for rectification of stereo pairs. Machine Vision and Applications, pp.16-22, 2000.

P. L. Combettes, A block-iterative surrogate constraint splitting method for quadratic signal recovery, IEEE Transactions on Signal Processing, vol.51, issue.7, pp.1771-1782, 1997.
DOI : 10.1109/TSP.2003.812846

E. Geoffrey and P. W. Richard, Detecting binocular half-occlusions: Empirical comparaisons of five approaches, IEEE Trans. Pattern Anal. Machine Intell, vol.42, issue.8, pp.1127-1133, 2002.

S. Osher and N. Paragios, Geometric Level Set Methods in Imaging, Vision and Graphics, 2003.

P. L. Combettes and J. C. Pesquet, Image Restoration Subject to a Total Variation Constraint, IEEE Transactions on Image Processing, vol.13, issue.9, pp.1213-1222, 2004.
DOI : 10.1109/TIP.2004.832922
URL : https://hal.archives-ouvertes.fr/hal-00017934

H. H. Nagel and W. Enkelmann, An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.8, issue.5, pp.565-593, 1986.
DOI : 10.1109/TPAMI.1986.4767833

M. Bleyer and M. Gelautz, A layered stereo algorithm using image segmentation and global visibility constraints, Int. Conf. Image Proc, pp.2997-3000, 2004.

M. Bleyer and M. Gelautz, Graph-based surface reconstruction from stereo pairs using image segmentation, Videometrics VIII, pp.288-299, 2005.
DOI : 10.1117/12.586502

C. Kim, K. M. Lee, B. T. Choi, and S. U. Lee, A dense stereo matching using two-pass dynamic programming with generalized ground control points, Computer Vision and Pattern Recognition, vol.2, pp.1075-1082, 2005.

Y. Deng, Q. Yang, X. Lin, and X. Tang, A symmetric patch-based correspondence model for occlusion handling, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.1316-1322, 2005.
DOI : 10.1109/ICCV.2005.23