Y. W. Aguilar, F. Frauel, M. E. Escolano, A. Martinez-perez, M. A. Espinosa-romero et al., A robust Graph Transformation Matching for non-rigid registration, Image and Vision Computing, vol.27, issue.7, pp.897-910, 2009.
DOI : 10.1016/j.imavis.2008.05.004

M. E. Antone and S. J. Teller, Scalable extrinsic calibration of omni-directional image networks, International Journal of Computer Vision, vol.49, issue.2/3, pp.143-174, 2002.
DOI : 10.1023/A:1020141505696

N. Ayache, Vision Stéréoscopique et Perception Multisensorielle : Application à la robotique mobile. Inter-Editions (MASSON), p.314, 1989.

M. Brown and D. Lowe, Automatic Panoramic Image Stitching using Invariant Features, International Journal of Computer Vision, vol.50, issue.1, pp.59-73, 2007.
DOI : 10.1007/s11263-006-0002-3

H. Bay, T. Tuytelaars, and L. Van-gool, SURF : Speeded Up Robust Features, Proc. of the European Conference on Computer Vision (ECCV), volume I of LNCS, pp.404-417, 2006.

A. Censi, A. Fusiello, and V. Roberto, Image stabilization by features tracking, Proceedings 10th International Conference on Image Analysis and Processing, pp.665-667, 1999.
DOI : 10.1109/ICIAP.1999.797671

. Clm-+-08-]-f, J. L. Cao, J. Lisani, P. Morel, F. Musé et al., A theory of shape identification. Number, Lecture Notes in Mathematics, issue.2, p.54, 1948.

O. Chum and J. Matas, Randomized RANSAC with T d,d test, Proc. of the British Machine Vision Conference (BMVC), p.55, 2002.

O. Chum and J. Matas, Matching with PROSAC ??? Progressive Sample Consensus, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.220-226, 2005.
DOI : 10.1109/CVPR.2005.221

URL : https://dspace.cvut.cz/bitstream/10467/9496/1/2005-Matching-with-PROSAC-progressive-sample-consensus.pdf

O. Chum and J. Matas, Optimal Randomized RANSAC, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.8, pp.1472-1482, 2008.
DOI : 10.1109/TPAMI.2007.70787

O. Chum, J. Matas, and J. Kittler, Locally Optimized RANSAC, Deutsche Arbeitsgemeinschaft für Mustererkennung (DAGM) Symposium, p.33, 2003.
DOI : 10.1007/978-3-540-45243-0_31

J. Domke and Y. Aloimonos, A Probabilistic Notion of Correspondence and the Epipolar Constraint, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06), p.49, 2006.
DOI : 10.1109/3DPVT.2006.18

A. Desolneux, L. Moisan, and J. Morel, Meaningful Alignments, International Journal of Computer Vision, vol.40, issue.1, pp.7-23, 2000.
DOI : 10.1023/A:1026593302236

A. Desolneux, L. Moisan, and J. Morel, From Gestalt theory to image analysis : a probabilistic approach. Interdisciplinary applied mathematics, p.54, 2008.
DOI : 10.1007/978-0-387-74378-3

URL : https://hal.archives-ouvertes.fr/hal-00259077

H. Deng, E. N. Mortensen, L. Shapiro, and T. G. Dietterich, Reinforcement Matching Using Region Context, Proc. of the IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), p.89, 2006.

F. Dellaert, S. M. Seitz, C. Thorpe, and S. Thrun, EM, MCMC, and chain flipping for structure from motion with unknown correspondence, Machine Learning, p.50, 2003.

M. Fischler and R. Bolles, Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, Communications of the ACM, vol.24, issue.6, pp.381-395, 1981.
DOI : 10.1145/358669.358692

M. A. Fischler and O. Firschein, Intelligence : The Eye, the Brain and the Computer, 1987.

O. Faugeras, Q. Luong, and T. Papadopoulou, The Geometry of Multiple Images, p.30, 2001.

D. A. Forsyth and J. Ponce, Computer Vision : A Modern Approach, p.10, 2002.
URL : https://hal.archives-ouvertes.fr/hal-01063327

D. Glasner, S. Bagon, and M. Irani, Super-resolution from a single image, 2009 IEEE 12th International Conference on Computer Vision, p.29, 2009.
DOI : 10.1109/ICCV.2009.5459271

P. F. Georgel, A. Bartoli, and N. Navab, Simultaneous in-plane motion estimation and point matching using geometric cues only, 2009 Workshop on Motion and Video Computing (WMVC), pp.1-7, 2009.
DOI : 10.1109/WMVC.2009.5399243

S. Gold and A. Rangarajan, A graduated assignment algorithm for graph matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, issue.4, pp.377-388, 1996.
DOI : 10.1109/34.491619

S. Gold, A. Rangarajan, C. Lu, S. Pappu, and E. Mjolsness, New algorithms for 2D and 3D point matching, Pattern Recognition, vol.31, issue.8, pp.311019-1031, 1998.
DOI : 10.1016/S0031-3203(98)80010-1

L. Goshen and I. Shimshoni, Balanced Exploration and Exploitation Model Search for Efficient Epipolar Geometry Estimation, Proc. of the European Conference on Computer Vision (ECCV), pp.151-164, 2006.

E. Hsiao, A. Collet, and M. Hebert, Making specific features less discriminative to improve point-based 3D object recognition, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.2010-2056
DOI : 10.1109/CVPR.2010.5539981

P. V. Hough, Machine analysis of bubble chamber pictures, International Conference on High Energy Accelerators and Instrumentation, p.31, 1959.

C. Harris and M. Stephens, A Combined Corner and Edge Detector, Procedings of the Alvey Vision Conference 1988, pp.147-151, 1921.
DOI : 10.5244/C.2.23

]. P. Hub81 and . Huber, Robust Statistics, p.31, 1981.

R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, pp.64-113, 2000.
DOI : 10.1017/CBO9780511811685

H. Jégou, M. Douze, and C. Schmid, On the burstiness of visual elements, 2009 IEEE Conference on Computer Vision and Pattern Recognition, p.94, 2009.
DOI : 10.1109/CVPR.2009.5206609

J. J. Koenderink, The structure of images, Biological Cybernetics, vol.27, issue.269, pp.363-370, 1984.
DOI : 10.1007/BF00336961

J. Krol and W. Van-der-grind, The Double-Nail Illusion: Experiments on Binocular Vision with Nails, Needles, and Pins, Perception, vol.16, issue.4, pp.651-659, 1980.
DOI : 10.1068/p090651

T. Kadir, A. Zisserman, and M. Brady, An Affine Invariant Salient Region Detector, Proc. of the European Conference on Computer Vision (ECCV), pp.345-457, 2004.
DOI : 10.1007/978-3-540-24670-1_18

]. S. Lbc-+-07, A. P. Lehmann, I. Bradley, L. Vaughan, J. Clarkson et al., Correspondence-free determination of the affine fundamental matrix, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.1, pp.82-97, 2007.

V. Lepetit and P. Fua, Keypoint recognition using randomized trees, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.9, pp.1465-1479, 2006.
DOI : 10.1109/TPAMI.2006.188

H. Longuet-higgins, A computer algorithm for reconstructing a scene from two projections, Nature, vol.194, issue.5828, pp.133-135, 1981.
DOI : 10.1038/293133a0

T. Lindeberg, Feature Detection with Automatic Scale Selection, International Journal of Computer Vision, vol.30, issue.2, pp.79-116, 1998.
DOI : 10.1023/A:1008045108935

H. Ling and K. Okada, Diffusion distance for histogram comparison, Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.246-253, 2006.

H. Ling and K. Okada, An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.5, pp.840-853, 2007.
DOI : 10.1109/TPAMI.2007.1058

D. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004.
DOI : 10.1023/B:VISI.0000029664.99615.94

J. Matas, O. Chum, M. Urban, and T. Pajdla, Robust wide-baseline stereo from maximally stable extremal regions, Image and Vision Computing, vol.22, issue.10, pp.761-767, 2004.
DOI : 10.1016/j.imavis.2004.02.006

N. D. Molton, A. J. Davison, and I. D. Reid, Locally Planar Patch Features for Real-Time Structure from Motion, Procedings of the British Machine Vision Conference 2004, p.93, 2004.
DOI : 10.5244/C.18.90

A. Makadia, C. Geyer, and K. Daniilidis, Correspondence-free Structure from Motion, International Journal of Computer Vision, vol.80, issue.2, pp.311-327, 2007.
DOI : 10.1007/s11263-007-0035-2

L. Moisan, Modèles continus, numériques et statistiques pour l'analyse d'images. Mémoire d'habilitation à diriger des recherches, 2003.

H. Moravec, Towards automatic visual obstacle avoidance, Proceedings of the 5th International Joint Conference on Artificial Intelligence, p.584, 1921.

H. Moravec, Obstacle Avoidance and Navigation in the Real World by a Seeing Robot Rover, 1922.

P. Moreels and P. Perona, Evaluation of Features Detectors and Descriptors based on 3D Objects, International Journal of Computer Vision, vol.59, issue.1, pp.263-284, 2007.
DOI : 10.1007/s11263-006-9967-1

K. Mikolajczyk and C. Schmid, Scale & Affine Invariant Interest Point Detectors, International Journal of Computer Vision, vol.60, issue.1, pp.63-86, 2004.
DOI : 10.1023/B:VISI.0000027790.02288.f2

URL : https://hal.archives-ouvertes.fr/inria-00548554

L. Moisan and B. Stival, A Probabilistic Criterion to Detect Rigid Point Matches Between Two Images and Estimate the Fundamental Matrix, International Journal of Computer Vision, vol.57, issue.3, pp.201-218, 2004.
DOI : 10.1023/B:VISI.0000013094.38752.54

URL : https://hal.archives-ouvertes.fr/hal-00171323

. Msc-+-06-]-p, F. Musé, F. Sur, Y. Cao, J. Gousseau et al., An a contrario decision method for shape element recognition, International Journal of Computer Vision, vol.69, issue.3, pp.295-315, 2006.

. Mts-+-06-]-k, T. Mikolajczyk, C. Tuytelaars, A. Schmid, J. Zisserman et al., A comparison of affine region detectors, International Journal of Computer Vision, vol.65, issue.62, pp.43-72, 2006.

J. Morel and G. Yu, ASIFT: A New Framework for Fully Affine Invariant Image Comparison, SIAM Journal on Imaging Sciences, vol.2, issue.2, pp.438-469, 1993.
DOI : 10.1137/080732730

D. Nistér, Preemptive RANSAC for Live Structure and Motion Estimation. Machine Vision and Applications, pp.321-329, 2005.

K. Ni, H. Jin, and F. Dellaert, Groupsac : Efficient consensus in the presence of groupings, Proc. of the International Conference of Computer Vision (ICCV), p.33, 2009.

N. Noury, F. Sur, and M. Berger, Fundamental Matrix Estimation Without Prior Match, 2007 IEEE International Conference on Image Processing, pp.513-516, 2007.
DOI : 10.1109/ICIP.2007.4379004

URL : https://hal.archives-ouvertes.fr/inria-00164807

N. Noury, F. Sur, and M. Berger, Modèles statistiques pour l'estimation de la matrice fondamentale, ORASIS, congrès francophone des jeunes chercheurs en vision par ordinateur, p.55, 2007.

N. Noury, F. Sur, and M. Berger, Determining point correspondences between two views under geometric constraint and photometric consistency, p.109, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00471874

N. Noury, F. Sur, and M. Berger, Modèle a contrario pour la mise en correspondance robuste sous contraintes épipolaires et photométriques, Actes de la conférence Reconnaissance de Formes et Intelligence Artificielle (RFIA), p.109, 2010.

N. Noury, F. Sur, and M. Berger, How to Overcome Perceptual Aliasing in ASIFT?, Proc. of the International Symposium on Visual Computing (ISVC), p.109, 2010.
DOI : 10.1007/978-3-642-17289-2_23

URL : https://hal.archives-ouvertes.fr/inria-00515375

M. Ozuysal, M. Calonder, V. Lepetit, and P. Fua, Fast Keypoint Recognition Using Random Ferns, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2009.
DOI : 10.1109/TPAMI.2009.23

M. Pollefeys, L. Van-gool, M. Vergauwen, F. Verbiest, K. Cornelis et al., Visual Modeling with a Hand-Held Camera, International Journal of Computer Vision, vol.59, issue.3, pp.207-232, 2004.
DOI : 10.1023/B:VISI.0000025798.50602.3a

S. Roy and I. J. Cox, Motion without structure, Proceedings of 13th International Conference on Pattern Recognition, pp.728-734, 1996.
DOI : 10.1109/ICPR.1996.546120

J. Rabin, J. Delon, and Y. Gousseau, A contrario matching of SIFT-like descriptors, 2008 19th International Conference on Pattern Recognition, p.27, 2008.
DOI : 10.1109/ICPR.2008.4761371

J. Rabin, J. Delon, and Y. Gousseau, Circular Earth Mover's Distance for the comparison of local features, Proc. of the International Conference on Pattern Recognition (ICPR), p.27, 2008.

J. Rabin, J. Delon, and Y. Gousseau, A Statistical Approach to the Matching of Local Features, SIAM Journal on Imaging Sciences, vol.2, issue.3, pp.931-958, 2009.
DOI : 10.1137/090751359

URL : https://hal.archives-ouvertes.fr/hal-00168285

J. Rabin, J. Delon, and Y. Gousseau, Transportation Distances on the Circle, Journal of Mathematical Imaging and Vision, vol.16, issue.6, p.28, 2009.
DOI : 10.1007/s10851-011-0284-0

URL : https://hal.archives-ouvertes.fr/hal-00399832

J. Rabin, J. Delon, Y. Gousseau, and L. Moisan, Mac-ransac : a robust algorithm for the recognition of multiple objects, Symposium on 3D Data Processing, Visualization and Transmission (3D'PVT), p.62, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00466487

R. Raguram, J. Frahm, and M. Pollefeys, A Comparative Analysis of RANSAC Techniques Leading to Adaptive Real-Time Random Sample Consensus, Proc. of the European Conference on Computer Vision (ECCV), pp.500-513, 2008.
DOI : 10.1007/978-3-540-88688-4_37

A. Rosenfeld, R. A. Hummel, and S. W. Zucker, Scene labeling by relaxation operations. Systems, Man and Cybernetics, IEEE Transactions on, vol.6, issue.6, pp.420-433, 1976.

P. Rousseeuw and A. Leroy, Robust Regression and Outlier Detection, p.31, 1987.
DOI : 10.1002/0471725382

R. Roberts, S. N. Sinha, R. Szeliski, and D. Steedly, Structure from motion for scenes with large duplicate structures, CVPR 2011, p.110, 2011.
DOI : 10.1109/CVPR.2011.5995549

Y. Rubner, C. Tomasi, and L. J. Guibas, The earth mover's distance as a metric for image retrieval, International Journal of Computer Vision, vol.40, issue.2, pp.99-121, 2000.
DOI : 10.1023/A:1026543900054

C. Schmid, Appariements d'images par invariants locaux de niveaux de gris, 1996.

C. Schmid, A structured probabilistic model for recognition, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149), pp.2485-89, 1999.
DOI : 10.1109/CVPR.1999.784725

URL : https://hal.archives-ouvertes.fr/inria-00548313

R. Sinkhorn, A Relationship Between Arbitrary Positive Matrices and Doubly Stochastic Matrices, The Annals of Mathematical Statistics, vol.35, issue.2, pp.876-879, 1964.
DOI : 10.1214/aoms/1177703591

C. Schmid and R. Mohr, Local grayvalue invariants for image retrieval, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.19, issue.5, pp.530-535, 1997.
DOI : 10.1109/34.589215

URL : https://hal.archives-ouvertes.fr/inria-00548358

R. Subbarao and P. Meer, Beyond RANSAC: User Independent Robust Regression, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06), pp.101-134, 2006.
DOI : 10.1109/CVPRW.2006.43

D. Sidibe, P. Montesinos, and S. Janaqi, Matching local invariant features with contextual information : An experimental evaluation, Electronic Letters on Computer Vision and Image Analysis, vol.7, issue.1, pp.26-39, 2008.
URL : https://hal.archives-ouvertes.fr/ujm-00357213

N. Snavely and . Bundler, Structure from motion (sfm) for unordered image collections, p.27

M. E. Serradell, V. Ozuysal, P. Lepetit, F. Fua, and . Moreno-noguer, Combining Geometric and Appearance Priors for Robust Homography Estimation, Proceedings of the European Conference on Computer Vision, p.93, 2010.
DOI : 10.1007/978-3-642-15558-1_5

G. P. Stein and A. Shashua, Model-based brightness constraints : on direct estimation of structure and motion. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.22, issue.9, pp.992-1015, 2000.

N. Snavely, S. M. Seitz, and R. Szeliski, Modeling the World from Internet Photo Collections, International Journal of Computer Vision, vol.17, issue.2, 2007.
DOI : 10.1007/s11263-007-0107-3

C. V. Stewart, MINPRAN: a new robust estimator for computer vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.17, issue.10, pp.925-938, 1995.
DOI : 10.1109/34.464558

F. Schaffalitzky and A. Zisserman, Planar grouping for automatic detection of vanishing lines and points, Image and Vision Computing, vol.18, issue.9, pp.647-658, 2000.
DOI : 10.1016/S0262-8856(99)00069-4

F. Schaffalitzky and A. Zisserman, Automated location matching in movies, Computer Vision and Image Understanding, vol.92, issue.2-3, pp.236-264, 2003.
DOI : 10.1016/j.cviu.2003.06.008

J. Sivic and A. Zisserman, Video Google: a text retrieval approach to object matching in videos, Proceedings Ninth IEEE International Conference on Computer Vision, pp.1470-1477, 2003.
DOI : 10.1109/ICCV.2003.1238663

D. Tell and S. Carlsson, Combining Appereance and Topology for Wide Baseline Matching, Proc. of the European Conference on Computer Vision (ECCV), number 2350 in LNCS, pp.68-81, 2002.

P. H. Torr, A. W. Fitzgibbon, and A. Zisserman, The Problem of Degeneracy in Structure and Motion Recovery from Uncalibrated Image Sequences, International Journal of Computer Vision, vol.32, issue.1, pp.27-44, 1999.
DOI : 10.1023/A:1008140928553

T. Tuytelaars and L. Van-gool, Matching Widely Separated Views Based on Affine Invariant Regions, International Journal of Computer Vision, vol.59, issue.1, pp.61-85, 2004.
DOI : 10.1023/B:VISI.0000020671.28016.e8

P. Torr and D. Murray, Outlier Detection and Motion Segmentation, Sensor Fusion VI, pp.432-443, 1993.

P. Torr and D. W. Murray, The development and comparison of robust methods for estimating the fundamental matrix, International Journal of Computer Vision, vol.24, issue.3, pp.271-300, 1997.
DOI : 10.1023/A:1007927408552

B. Tordoff and D. W. Murray, Guided Sampling and Consensus for Motion Estimation, Proc. of the European Conference on Computer Vision (ECCV), pp.82-98, 2002.
DOI : 10.1007/3-540-47969-4_6

B. J. Tordoff and D. W. Murray, Guided-MLESAC: faster image transform estimation by using matching priors, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.27, issue.10, pp.1523-1535, 2005.
DOI : 10.1109/TPAMI.2005.199

T. Tuytelaars and K. Mikolajczyk, Local invariant feature detectors : a survey. Foundations and Trends in Computer Graphics and Vision, pp.177-280, 2008.

P. Torr, Bayesian model estimation and selection for epipolar geometry and generic manifold fitting, International Journal of Computer Vision, vol.50, issue.1, pp.35-61, 2002.
DOI : 10.1023/A:1020224303087

P. Torr and A. Zisserman, MLESAC: A New Robust Estimator with Application to Estimating Image Geometry, Computer Vision and Image Understanding, vol.78, issue.1, pp.138-156, 2000.
DOI : 10.1006/cviu.1999.0832

A. Vedaldi and B. Fulkerson, Vlfeat, Proceedings of the international conference on Multimedia, MM '10, p.98, 2008.
DOI : 10.1145/1873951.1874249

S. D. Whitehead and D. H. Ballard, Learning to perceive and act by trial and error, Machine Learning, pp.45-83, 1991.
DOI : 10.1007/BF00058926

]. Wu, B. Clipp, X. Li, J. Frahm, and M. Pollefeys, 3d model matching with viewpoint-invariant patches (vip), Computer Vision and Pattern Recognition CVPR 2008. IEEE Conference on, pp.1-8, 2008.

Z. Zhang, R. Deriche, O. D. Faugeras, and Q. Luong, A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry, Artificial Intelligence, vol.78, issue.1-2, pp.87-119, 1995.
DOI : 10.1016/0004-3702(95)00022-4

URL : https://hal.archives-ouvertes.fr/inria-00074398

Z. Zhang, Determining the epipolar geometry and its uncertainty : a review, International Journal of Computer Vision, vol.27, issue.2, pp.161-195, 1998.
DOI : 10.1023/A:1007941100561

URL : https://hal.archives-ouvertes.fr/inria-00073771

W. Zhang and J. Kosecka, Generalized RANSAC Framework for Relaxed Correspondence Problems, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06), pp.854-860, 2006.
DOI : 10.1109/3DPVT.2006.67