P. J. Besl and N. D. Mckay, A method for registration of 3-D shapes, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.2, pp.239-256, 1992.
DOI : 10.1109/34.121791

A. W. Fitzgibbon, Robust registration of 2D and 3D point sets, Image and Vision Computing, vol.21, issue.13-14, pp.1145-1153, 2001.
DOI : 10.1016/j.imavis.2003.09.004
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.21.4197

Y. Tsin and T. Kanade, A Correlation-Based Approach to Robust Point Set Registration, European Conference on Computer Vision, 2004.
DOI : 10.1007/978-3-540-24672-5_44
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.6729

A. Myronenko and X. Song, Point Set Registration: Coherent Point Drift, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.12, pp.2262-2275, 2010.
DOI : 10.1109/TPAMI.2010.46
URL : http://arxiv.org/abs/0905.2635

R. Horaud, F. Forbes, M. Yguel, G. Dewaele, and J. Zhang, Rigid and Articulated Point Registration with Expectation Conditional Maximization, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.3, pp.587-602, 2011.
DOI : 10.1109/TPAMI.2010.94
URL : https://hal.archives-ouvertes.fr/inria-00435772

B. Jian and B. C. Vemuri, Robust Point Set Registration Using Gaussian Mixture Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.8, pp.1633-1645, 2011.
DOI : 10.1109/TPAMI.2010.223

J. Williams and M. Bennamoun, Simultaneous Registration of Multiple Corresponding Point Sets, Computer Vision and Image Understanding, vol.81, issue.1, pp.117-142, 2001.
DOI : 10.1006/cviu.2000.0884

F. Wang, B. C. Vemuri, A. Rangarajan, and S. J. Eisenschenk, Simultaneous Nonrigid Registration of Multiple Point Sets and Atlas Construction, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.11, pp.2011-2022, 2008.
DOI : 10.1109/TPAMI.2007.70829
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2921641/pdf

V. M. Govindu and A. Pooja, On Averaging Multiview Relations for 3D Scan Registration, IEEE Transactions on Image Processing, vol.23, issue.3, pp.1289-1302, 2014.
DOI : 10.1109/TIP.2013.2246517

G. Blais and M. D. Levine, Registering multiview range data to create 3D computer objects, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.17, issue.8, pp.820-824, 1995.
DOI : 10.1109/34.400574
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.2506

T. Masuda and N. Yokoya, A Robust Method for Registration and Segmentation of Multiple Range Images, Computer Vision and Image Understanding, vol.61, issue.3, pp.295-307, 1995.
DOI : 10.1006/cviu.1995.1024

S. Izadi, D. Kim, O. Hilliges, D. Molyneaux, R. Newcombe et al., KinectFusion, Proceedings of the 24th annual ACM symposium on User interface software and technology, UIST '11, 2011.
DOI : 10.1145/2047196.2047270

R. Bergevin, M. Soucy, H. Gagnon, and D. Laurendeau, Towards a general multi-view registration technique, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, issue.5, pp.540-547, 1996.
DOI : 10.1109/34.494643

U. Castellani, A. Fusiello, and V. Murino, Registration of Multiple Acoustic Range Views for Underwater Scene Reconstruction, Computer Vision and Image Understanding, vol.87, issue.1-3, pp.78-89, 2002.
DOI : 10.1006/cviu.2002.0984

D. F. Huber and M. Hebert, Fully automatic registration of multiple 3D data sets, Image and Vision Computing, vol.21, issue.7, pp.637-650, 2003.
DOI : 10.1016/S0262-8856(03)00060-X
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.25.5660

S. Shih, Y. Chuang, and T. Yu, An Efficient and Accurate Method for the Relaxation of Multiview Registration Error, IEEE Transactions on Image Processing, vol.17, issue.6, pp.968-981, 2008.
DOI : 10.1109/TIP.2008.921987

J. D. Banfield and A. E. Raftery, Model-Based Gaussian and Non-Gaussian Clustering, Biometrics, vol.49, issue.3, pp.803-821, 1993.
DOI : 10.2307/2532201

G. Evangelidis, D. Kounades-bastian, R. Horaud, and E. Psarakis, A Generative Model for the Joint Registration of Multiple Point Sets, European Conference on Computer Vision, 2014.
DOI : 10.1007/978-3-319-10584-0_8
URL : https://hal.archives-ouvertes.fr/hal-01019661

Y. Chen and G. Medioni, Object modelling by registration of multiple range images, Image and Vision Computing, vol.10, issue.3, pp.145-155, 1992.
DOI : 10.1016/0262-8856(92)90066-C

D. Chetverikov, D. Svirko, D. Stepanov, and P. Krsek, The Trimmed Iterative Closest Point algorithm, Object recognition supported by user interaction for service robots, 2002.
DOI : 10.1109/ICPR.2002.1047997
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.2020

J. Yang, H. Li, and Y. Jia, Go-ICP: Solving 3D Registration Efficiently and Globally Optimally, 2013 IEEE International Conference on Computer Vision, 2013.
DOI : 10.1109/ICCV.2013.184
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.648.5379

W. Wells and I. , Statistical approaches to feature-based object recognition, International Journal of Computer Vision, vol.28, issue.12, pp.63-98, 1997.

S. Granger and X. Pennec, Multi-scale EM-ICP: A Fast and Robust Approach for Surface Registration, European Conference on Computer Vision, 2002.
DOI : 10.1007/3-540-47979-1_28
URL : https://hal.archives-ouvertes.fr/inria-00615911

H. Chui and A. Rangarajan, A new point matching algorithm for non-rigid registration, Computer Vision and Image Understanding, vol.89, issue.2-3, pp.114-141, 2003.
DOI : 10.1016/S1077-3142(03)00009-2
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.7.4365

J. Hermans, D. Smeets, D. Vandermeulen, and P. Suetens, Robust point set registration using EM-ICP with information-theoretically optimal outlier handling, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995744

R. Benjemaa and F. Schmitt, A solution for the registration of multiple 3D point sets using unit quaternions, European Conference on Computer Vision, pp.34-50, 1998.
DOI : 10.1007/BFb0054732

T. Masuda, Registration and Integration of Multiple Range Images by Matching Signed Distance Fields for Object Shape Modeling, Computer Vision and Image Understanding, vol.87, issue.1-3, pp.51-65, 2002.
DOI : 10.1006/cviu.2002.0982

G. C. Sharp, S. W. Lee, and D. K. Wehe, Multiview registration of 3D scenes by minimizing error between coordinate frames, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.8, pp.1037-1050, 2004.
DOI : 10.1109/TPAMI.2004.49

S. Krishnan, P. Y. Lee, and J. B. Moore, Optimisation-on-a-manifold for global registration of multiple 3D point sets, International Journal of Intelligent Systems Technologies and Applications, vol.3, issue.3/4, pp.319-340, 2007.
DOI : 10.1504/IJISTA.2007.014267

A. Torsello, E. Rodol, and A. A. , Multiview registration via graph diffusion of dual quaternions, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995565

Y. Peng, A. Ganesh, J. Wright, W. Xu, and Y. Ma, RASL: Robust alignment by sparse and low-rank decomposition for linearly correlated images, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.2233-2246, 2012.
DOI : 10.1109/CVPR.2010.5540138
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.171.472

D. Thomas, Y. Matsushita, and A. Sugimoto, Robust Simultaneous 3D Registration via Rank Minimization, 2012 Second International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission, pp.33-40, 2012.
DOI : 10.1109/3DIMPVT.2012.15

V. M. Govindu, Combining two-view constraints for motion estimation, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001.
DOI : 10.1109/CVPR.2001.990963
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.19.847

R. Hartley, J. Trumpf, Y. Dai, and H. Li, Rotation Averaging, International Journal of Computer Vision, vol.14, issue.4, pp.267-305, 2013.
DOI : 10.1109/70.704231

Z. Li, J. Zhu, K. Lan, C. Li, and C. Fang, Improved techniques for multi-view registration with motion averaging, IEEE Conference on 3D Vision, 2014.

D. Chetverikov, D. Stepanov, and P. Krsek, Robust Euclidean alignment of 3D point sets: the trimmed iterative closest point algorithm, Image and Vision Computing, vol.23, issue.3, pp.299-309, 2005.
DOI : 10.1016/j.imavis.2004.05.007

G. Cui, S. Schuon, S. Thrun, D. Stricker, and C. Theobalt, Registration of multiple point sets using the EM algorithm Algorithms for 3D shape scanning with a depth camera, IEEE International Conference on Computer Vision, pp.1039-1050, 1999.

X. Mateo, X. Orriols, and X. Binefa, Bayesian perspective for the registration of multiple 3D views, Computer Vision and Image Understanding, vol.118, pp.84-96, 2014.
DOI : 10.1016/j.cviu.2013.09.003

M. Danelljan, G. Meneghetti, F. Khan, and M. Felsberg, A Probabilistic Framework for Color-Based Point Set Registration, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
DOI : 10.1109/CVPR.2016.201

T. Shiratori, J. Berclaz, M. Harville, C. Shah, T. Li et al., Efficient Large-Scale Point Cloud Registration Using Loop Closures, 2015 International Conference on 3D Vision, 2015.
DOI : 10.1109/3DV.2015.33

C. Bishop, Pattern Recognition and Machine Learning, 2006.

X. Meng and D. B. Rubin, Maximum likelihood estimation via the ECM algorithm: A general framework, Biometrika, vol.80, issue.2, pp.267-278, 1993.
DOI : 10.1093/biomet/80.2.267

S. Umeyama, Least-squares estimation of transformation parameters between two point patterns, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.13, issue.4, pp.376-380, 1991.
DOI : 10.1109/34.88573

M. Hansard, R. Horaud, M. Amat, and G. Evangelidis, Automatic detection of calibration grids in time-of-flight images, Computer Vision and Image Understanding, vol.121, pp.108-118, 2014.
DOI : 10.1016/j.cviu.2014.01.007
URL : https://hal.archives-ouvertes.fr/hal-00936333

M. Hansard, G. Evangelidis, Q. Pelorson, and R. Horaud, Cross-calibration of time-of-flight and colour cameras, Computer Vision and Image Understanding, vol.134, pp.105-115, 2015.
DOI : 10.1016/j.cviu.2014.09.001
URL : https://hal.archives-ouvertes.fr/hal-01019668

J. Sturm, N. Engelhard, F. Endres, W. Burgard, and D. Cremers, A benchmark for the evaluation of RGB-D SLAM systems, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012.
DOI : 10.1109/IROS.2012.6385773

R. Mur-artal and J. D. Tardos, ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras, IEEE Transactions on Robotics, 2016.
DOI : 10.1109/TRO.2017.2705103

T. Whelan, R. F. Salas-moreno, B. Glocker, A. J. Davison, and S. Leutenegger, ElasticFusion: Real-time dense SLAM and light source estimation, The International Journal of Robotics Research, vol.35, issue.14, pp.1697-1716, 2016.
DOI : 10.1109/ICCV.2013.65
URL : http://spiral.imperial.ac.uk/bitstream/10044/1/39502/4/Whelan16ijrr.pdf

F. Endres, J. Hess, J. Sturm, D. Cremers, and W. Burgard, 3-D Mapping With an RGB-D Camera, IEEE Transactions on Robotics, vol.30, issue.1, pp.177-187, 2014.
DOI : 10.1109/TRO.2013.2279412

B. Eckart, K. Kim, A. Troccoli, and A. Kelly, Accelerated generative models, IEEE Computer Vision and Pattern Recognition, 2016.
DOI : 10.1109/cvpr.2016.593