N. Canterakis, A Minimal Set of Constraints for the Trifocal Tensor, pp.84-99
DOI : 10.1007/3-540-45054-8_6

O. Faugeras and T. Papadopoulo, A nonlinear method for estimating the projective geometry of 3 views, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), pp.477-484, 1998.
DOI : 10.1109/ICCV.1998.710761

R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, second edn, p.521540518, 2004.

M. Havlena, A. Torii, J. Knopp, and T. Pajdla, Randomized structure from motion based on atomic 3D models from camera triplets, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.2874-28815206677, 2009.
DOI : 10.1109/CVPR.2009.5206677

K. Levenberg, A method for the solution of certain non-linear problems in least squares, Quarterly of Applied Mathematics, vol.2, issue.2, pp.164-16843633451, 1944.
DOI : 10.1090/qam/10666

Y. Ma, K. Huang, R. Vidal, J. Ko?ecká, and S. Sastry, Rank Conditions on the Multiple-View Matrix, International Journal of Computer Vision, vol.59, issue.2, pp.115-137, 2004.
DOI : 10.1023/B:VISI.0000022286.53224.3d
URL : http://black.csl.uiuc.edu/~yima/psfile/rank-3d.ps.gz

P. Moulon, P. Monasse, and R. Marlet, Adaptive Structure from Motion with a??Contrario Model Estimation, Asian Conference on Computer Vision, pp.257-270, 2012.
DOI : 10.1007/978-3-642-37447-0_20
URL : https://hal.archives-ouvertes.fr/hal-00769266

P. Moulon, P. Monasse, and R. Marlet, Global Fusion of Relative Motions for Robust, Accurate and Scalable Structure from Motion, 2013 IEEE International Conference on Computer Vision, pp.3248-3255, 2013.
DOI : 10.1109/ICCV.2013.403
URL : https://hal.archives-ouvertes.fr/hal-00873504

F. Neitzel, Generalization of total least-squares on example of unweighted and weighted 2D similarity transformation, Journal of Geodesy, vol.432, issue.8, pp.751-762, 2010.
DOI : 10.1137/1.9781611971002

K. Nordberg, A minimal parameterization of the trifocal tensor, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.1224-1230, 2009.
DOI : 10.1109/CVPR.2009.5206829

T. Papadopoulo and O. Faugeras, A new characterization of the trifocal tensor, pp.109-123, 1998.
DOI : 10.1007/BFb0055662

J. Ponce and M. Hebert, Trinocular Geometry Revisited, 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.17-24, 2014.
DOI : 10.1109/CVPR.2014.10
URL : https://hal.archives-ouvertes.fr/hal-01053676

C. Ressl, A minimal set of constraints and a minimal parameterization for the trifocal tensor In: The International Archives of the Photogrammetry, XXXIV, Part 3A, ISPRS-Comm. III Symposium, p.13, 2002.

J. L. Schönberger and J. M. Frahm, Structure-from-Motion Revisited, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
DOI : 10.1109/CVPR.2016.445

N. Snavely, Bundler: Structure from motion for unordered image collections (2010). https

C. Strecha, W. Von-hansen, L. V. Gool, P. Fua, and U. Thoennessen, On benchmarking camera calibration and multi-view stereo for high resolution imagery, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587706
URL : https://infoscience.epfl.ch/record/126393/files/strecha_cvpr_2008.pdf

P. Torr and A. Zisserman, Robust parameterization and computation of the trifocal tensor, Image and Vision Computing, vol.15, issue.8, pp.591-605, 1997.
DOI : 10.1016/S0262-8856(97)00010-3