D. , A. Haubold, C. Avidan, S. And-hamprecht, and F. A. , Semi-global matching : a principled derivation in terms of message passing, German Conference on Pattern Recognition, pp.43-53, 2014.

F. , G. Franchis, C. D. , A. Mein-hardt, and E. , MGM : A Significantly More Global Matching for Stereovision, BMVC 2015
URL : https://hal.archives-ouvertes.fr/hal-01240853

F. , P. F. And-huttenlocher, and D. P. , Efficient belief propagation for early vision, International Journal of Computer Vision, vol.70, issue.1, pp.41-54, 2006.

H. , J. M. Jeon, B. Jeon, J. Jo, S. Y. And-jeong et al., Cost aggregation table : a theoretic derivation on the markov random field and its relation to message passing, Image Processing (ICIP), 2015 IEEE International Conference on, pp.2224-2228, 2015.

H. , S. And-klette, and R. , Iterative semiglobal matching for robust driver assistance systems, Asian Conference on Computer Vision, pp.465-478, 2012.

H. , S. Klette, R. And-destefanis, and E. , Inclusion of a second-order prior into semiglobal matching, Advances in Image and Video Technology, pp.633-644, 2009.

H. and H. , Stereo processing by semiglobal matching and mutual information, IEEE Transactions, vol.30, issue.2, pp.328-341, 2008.

H. , H. And-scharstein, and D. , Evaluation of cost functions for stereo matching, Computer Vision and Pattern Recognition CV- PR'07. IEEE Conference on, pp.1-8, 2007.

M. , M. And-geiger, and A. , Object scene flow for autonomous vehicles, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.3061-3070, 2015.

P. and M. , Optimisation discrète et indices de stabilité appliqués à la stéréoscopie en contexte routier, 2017.

P. , M. Tarel, J. And-monasse, and P. , Stereo ambiguity index for semi-global matching, Proceedings of IEEE International Conference on Image Processing (ICIP'17), pp.2513-2517
URL : https://hal.archives-ouvertes.fr/hal-01592680

M. Park and K. And-yoon, Leveraging stereo matching with learning-based confidence measures, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.101-109, 2015.

S. , D. Hirschmüller, H. Kitajima, Y. Krathwohl, G. Ne?i´cne?i´-ne?i´c et al., High-resolution stereo datasets with subpixel-accurate ground truth, German Conference on Pattern Recognition, pp.31-42, 2014.

S. , D. And-szeliski, and R. , A taxonomy and evaluation of dense two-frame stereo correspondence algorithms, International Journal of Computer Vision, vol.47, issue.1, pp.7-42, 2002.

S. , D. And-szeliski, and R. , High-accuracy stereo depth maps using structured light, Computer Vision and Pattern Recognition Proceedings. 2003 IEEE Computer Society Conference on, p.I?I, 2003.

S. , A. And-pollefeys, and M. , Patch based confidence prediction for dense disparity map, British Machine Vision Conference (BMVC), 2016.

O. Veksler, Efficient graph-based energy minimization methods in computer vision, 1999.

Z. , R. And-woodfill, and J. , Non-parametric local transforms for computing visual correspondence, European conference on computer vision, pp.151-158, 1994.

Z. , K. Lu, J. And-lafruit, and G. , Crossbased local stereo matching using orthogonal integral images, pp.1073-1079, 2009.