I. Araya, G. Trombettoni, B. Neveu, and G. Chabert, Upper Bounding in Inner Regions for Global Optimization under Inequality Constraints, J. Global Optimization (JOGO), vol.60, issue.2, pp.145-164, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00733860

J. C. Bazin, Y. Seo, R. Hartley, and M. Pollefeys, Globally Optimal Inlier Set Maximization With Unknown Rotation and Focal Length, Proc. of European Conference of Computer Vision (ECCV), vol.8690, pp.803-817, 2014.

F. Benhamou, F. Goualard, L. Granvilliers, and J. F. Puget, Revising Hull and Box Consistency, Proc. of International Conference on Logic Programming (ICLP), pp.230-244, 1999.

A. Bethencourt and L. Jaulin, 3D Reconstruction Using Interval Methods on the Kinect Device Coupled with an IMU, Int. Journal of Advanced Robotic Systems, vol.10, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00807450

D. Campbell, L. Peterson, L. Kneip, and H. Li, Globally-Optimal Inlier Set Maximisation for Simultaneous Camera Pose and Feature Correspondence, IEEE International Conference on Computer Vision (ICCV, 2017.

C. Carbonnel, G. Trombettoni, P. Vismara, and G. Chabert, Q-Intersection Algorithms for Constrained-Based Robust Parameter Estimation, Proc. of Conference of the Association for the Advancement of Artificial Intelligence (AAAI), pp.2630-2636, 2014.

G. Chabert and L. Jaulin, Contractor Programming, vol.173, pp.1079-1100, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00428957

B. Neveu,

P. Chew and K. Marzullo, Masking Failures of Multidimensional Sensors, Proc. of Reliable Distributed Systems, pp.32-41, 1991.

T. J. Chin, P. Purkait, A. Eriksson, and D. Suter, Efficient Globally Optimal Consensus Maximisation with Tree Search, Proc. of CVPR 15, 2015.

T. J. Chin, P. Purkait, A. Eriksson, and D. Suter, Efficient Globally Optimal Consensus Maximisation with Tree Search, IEEE Trans. Pattern Anal. Mach. Intell, vol.39, issue.4, pp.758-772, 2017.

H. Collavizza, F. Delobel, and M. Rueher, Comparing Partial Consistencies. Reliable Computing, vol.5, issue.3, pp.213-228, 1999.

M. A. Fischler and R. C. Bolles, Random Sampling Consensus: a Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography, Commun. of the ACM, vol.24, issue.6, pp.381-395, 1981.

A. Fusiello, A. Benedetti, M. Farenzena, and A. Busti, Globally Convergent Autocalibration Using Interval Analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.12, pp.1633-1638, 2004.

R. Hartley and F. Kahl, Global Optimization through Searching Rotation Space and Optimal Estimation of the Essential Matrix, Proceedings of ICCV, 2007.

R. Hartley and A. Zisserman, Multiple view geometry in computer vision, 2003.

L. Jaulin and S. Bazeille, Image Shape Extraction using Interval Methods, Proc. of the 16th IFAC Symposium on System, pp.378-383, 2009.

L. Jaulin and E. Walter, Guaranteed Robust Nonlinear Minimax Estimation, IEEE Trans. on Automatic Control, vol.47, 2002.
URL : https://hal.archives-ouvertes.fr/hal-00845633

L. Jaulin, E. Walter, and O. Didrit, Guaranteed Robust Nonlinear Parameter Bounding, CESA'96 IMACS Multiconference (Symposium on Modelling, Analysis and Simulation), pp.1156-1161, 1996.

K. Lai and D. Fox, Object recognition in 3d point clouds using web data and domain adaptation, International Journal of Robotics Research, vol.29, issue.8, pp.1019-1037, 2010.

H. C. Longuet-higgins, A Computer Algorithm for Reconstructing a Scene from two Projections, Nature, vol.293, issue.5828, pp.133-135, 1981.

F. Messine, Méthodes d'optimisation globale basées sur l'analyse d'intervalle pour la résolution desprobì emes avec contraintes, 1997.

R. Misener and C. Floudas, ANTIGONE: Algorithms for coNTinuous / Integer Global Optimization of Nonlinear Equations, J. Global Optimization (JOGO), vol.59, issue.2, pp.503-526, 2014.

L. Moisan, P. Moulon, and P. Monasse, Fundamental Matrix of a Stereo Pair, with A Contrario Elimination of Outliers, Image Processing On Line, vol.6, pp.89-113, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01386806

B. Neveu, M. De-la-gorce, and G. Trombettoni, Improving a Constraint Programming Approach for Parameter Estimation, 27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), pp.852-859, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01230041

B. Neveu, G. Trombettoni, and I. Araya, Adaptive Constructive Interval Disjunction: Algorithms and Experiments, Constraints Journal, vol.20, issue.7, pp.452-467, 2015.
DOI : 10.1007/s10601-015-9180-3
URL : https://hal.archives-ouvertes.fr/hal-01119535

B. Neveu, G. Trombettoni, and I. Araya, Node Selection Strategies in Interval Branch and Bound Algorithms, Journal of Global Optimization, vol.64, issue.2, pp.289-304, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01230893

J. Ninin, F. Messine, and P. Hansen, A Reliable Affine Relaxation Method for Global Optimization, vol.4, pp.1-31, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01194735

D. Nistér, An efficient solution to the five-point relative pose problem, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.6, pp.756-770, 2004.

R. Raguram, O. Chum, M. Pollefeys, J. Matas, and J. M. Frahm, Usac: A universal framework for random sample consensus, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.8, 2013.

R. Schnabel, R. Wahl, and R. Klein, Efficient RANSAC for Point-Cloud Shape Detection, Computer Graphics Forum, vol.26, issue.2, pp.214-226, 2007.

M. Tawarmalani and N. V. Sahinidis, A Polyhedral Branch-and-Cut Approach to Global Optimization, Mathematical Programming, vol.103, issue.2, pp.225-249, 2005.
DOI : 10.1007/s10107-005-0581-8

G. Trombettoni, I. Araya, B. Neveu, and G. Chabert, Inner Regions and Interval Linearizations for Global Optimization, Proc. AAAI, pp.99-104, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00648085

P. Van-hentenryck, L. Michel, and Y. Deville, Numerica : A Modeling Language for Global Optimization, 1997.

J. Yang, H. Li, and Y. Jia, Optimal Essential Matrix Optimization via Inlier-Set Maximization, Proc. of European Conference of Computer Vision (ECCV), pp.111-126, 2014.
DOI : 10.1007/978-3-319-10590-1_8