]. T. Botterill, S. Mills, and R. Green, New Conditional Sampling Strategies for Speeded-Up RANSAC, Procedings of the British Machine Vision Conference 2009, 2009.
DOI : 10.5244/C.23.33

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, T. Werner, and J. Matas, Two-View Geometry Estimation Unaffected by a Dominant Plane, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.772-779, 2005.
DOI : 10.1109/CVPR.2005.354

A. Martin, R. C. Fischler, and . 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.

J. Frahm and M. Pollefeys, RANSAC for (Quasi-)Degenerate data (QDEGSAC), 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1 (CVPR'06), pp.453-460, 2006.
DOI : 10.1109/CVPR.2006.235
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.123.9404

S. Laveau and O. Faugeras, Oriented projective geometry for computer vision, ECCV96, pp.147-156, 1996.
DOI : 10.1007/BFb0015531
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.6161

G. David and . Lowe, Distinctive image features from scale-invariant keypoints, Int. J. Comput. Vision, vol.60, issue.2, pp.91-110, 2004.

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

D. R. Myatt, P. H. Torr, S. J. Nasuto, J. M. Bishop, and R. Craddock, NAPSAC: High Noise, High Dimensional Robust Estimation - it's in the Bag, Procedings of the British Machine Vision Conference 2002, 2002.
DOI : 10.5244/C.16.44

K. Ni, H. Jin, and F. Dellaert, Groupsac: Efficient consensus in the presence of groupings, ICCV09, Kyoto;Japan, 2009.

J. Ben, D. W. Tordoff, and . Murray, Guided-mlesac: Faster image transform estimation by using matching priors, IEEE Trans. Pattern Anal. Mach. Intell, vol.27, issue.10, pp.1523-1535, 0199.

T. Werner and T. Pajdla, Oriented Matching Constraints, Procedings of the British Machine Vision Conference 2001, 2001.
DOI : 10.5244/C.15.46
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.3.1548

L. Zelnik-manor and M. Irani, Multiview constraints on homographies, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.2, pp.214-223, 2002.
DOI : 10.1109/34.982901