D. Aouada, S. Feng, and H. Krim, Statistical Analysis of the Global Geodesic Function for 3D Object Classification, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07, pp.645-648, 2007.
DOI : 10.1109/ICASSP.2007.365990

N. Aronszajn, Theory of reproducing kernels. Transactions of the, pp.337-404, 1950.

A. Basu, I. R. Harri, N. L. Hjort, and M. C. Jones, Robust and efficient estimation by minimising a density power divergence, Biometrika, vol.85, issue.3, pp.549-559, 1998.
DOI : 10.1093/biomet/85.3.549

J. L. Bentley, Multidimensional binary search trees used for associative searching, Communications of the ACM, vol.18, issue.9, pp.509-517, 1975.
DOI : 10.1145/361002.361007

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

F. L. Bookstein, Principal warps: thin-plate splines and the decomposition of deformations, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.11, issue.6, pp.567-585, 1989.
DOI : 10.1109/34.24792

V. Camion and L. Younes, Geodesic Interpolating Splines, International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, pp.513-527, 2001.
DOI : 10.1007/3-540-44745-8_34
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.7394

M. Carcassoni and E. R. Hancock, Spectral Correspondence for Deformed Point-Set Matching, International Workshop on Articulated Motion and Deformable Objects, pp.120-132, 2000.
DOI : 10.1007/10722604_11

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.44-51, 2000.
DOI : 10.1016/S1077-3142(03)00009-2

H. Chui and A. Rangarajan, A new point matching algorithm for non-rigid registration, IEEE Conference on Computer Vision and Pattern Recognition, pp.44-51, 2000.
DOI : 10.1016/S1077-3142(03)00009-2

N. E. Day, Estimating the components of a mixture of normal distributions, Biometrika, vol.56, issue.3, pp.463-474, 1969.
DOI : 10.1093/biomet/56.3.463

A. Dedner, M. Lüthi, T. Albrecht, and T. Vetter, Curvature Guided Level Set Registration Using Adaptive Finite Elements, IEEE Conference on Pattern recognition, pp.527-536, 2007.
DOI : 10.1007/978-3-540-74936-3_53
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.88.2506

A. P. Dempster, N. M. Laird, and D. B. Rubin, Maximum Likelihood from Incomplete Data via the EM Algorithm, Journal of the Royal Statistical Society. Series B (Methodological), vol.39, issue.1, pp.1-38, 1977.

J. Feldmar and N. Ayache, Rigid, affine and locally affine registration of free-form surfaces, International Journal of Computer Vision, vol.13, issue.2, pp.99-119, 1996.
DOI : 10.1007/BF00054998
URL : https://hal.archives-ouvertes.fr/inria-00074451

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

G. Celeux and G. Govaert, A classification EM algorithm for clustering and two stochastic versions, Computational Statistics & Data Analysis, vol.14, issue.3, pp.315-332, 1992.
DOI : 10.1016/0167-9473(92)90042-E
URL : https://hal.archives-ouvertes.fr/inria-00075196

D. Geman and G. Reynolds, Constrained restoration and the recovery of discontinuities, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.3, pp.367-383, 1992.
DOI : 10.1109/34.120331

J. Glaunes, A. Trouvé, and L. Younes, Diffeomorphic matching of distributions: a new approach for unlabelled point-sets and sub-manifolds matching, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., pp.712-718, 2004.
DOI : 10.1109/CVPR.2004.1315234

S. Granger and X. Pennec, Multi-scale EM-ICP: A Fast and Robust Approach for Surface Registration, European Conference on Computer Vision, pp.418-432, 2002.
DOI : 10.1007/3-540-47979-1_28
URL : https://hal.archives-ouvertes.fr/inria-00615911

P. J. Green, On Use of the EM for Penalized Likelihood Estimation, Journal of the Royal Statistical Society. Series B (Methodological), vol.52, issue.3, pp.443-452, 1990.

L. Greengard and J. Strain, The Fast Gauss Transform, SIAM Journal on Scientific and Statistical Computing, vol.12, issue.1, pp.79-94, 1991.
DOI : 10.1137/0912004

S. Gumhold, X. Wang, and R. Macleod, Feature Extraction from Point Clouds, Proceedings of the 10th International Meshing Roundtable, pp.293-305, 2001.

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, 2010.
DOI : 10.1109/TPAMI.2010.94
URL : https://hal.archives-ouvertes.fr/inria-00435772

Q. Huang, B. Adams, M. Wicke, and L. J. Guibas, Non-Rigid Registration Under Isometric Deformations, Computer Graphics Forum, vol.26, issue.3, pp.1449-1457, 2008.
DOI : 10.1111/j.1467-8659.2008.01285.x

B. Jian and B. C. Vemuri, A robust algorithm for point set registration using mixture of gaussians, IEEE International Conference on Computer Vision, pp.1246-1251, 2005.

S. C. Joshi and M. I. Miller, Landmark matching via large deformation diffeomorphisms, IEEE Transactions on Image Processing, vol.9, issue.8, pp.1357-1370, 2000.
DOI : 10.1109/83.855431

J. J. Koenderink and A. J. Van-doorn, Surface shape and curvature scales, Image and Vision Computing, vol.10, issue.8, pp.557-564, 1992.
DOI : 10.1016/0262-8856(92)90076-F

M. Lüthi, T. Albrecht, and T. Vetter, Curvature guided surface registration using level sets, Congress on Computer Assisted Radiology and Surgery, 2007.

J. B. Maintz and M. A. Viergever, A survey of medical image registration, Medical Image Analysis, vol.2, issue.1, pp.1-36, 1998.
DOI : 10.1016/S1361-8415(01)80026-8

F. H. Marriott, 389: Separating Mixtures of Normal Distributions, Biometrics, vol.31, issue.3, pp.31767-769, 1975.
DOI : 10.2307/2529563

D. Mateus, R. P. Horaud, D. Knossow, F. Cuzzolin, and E. Boyer, Articulated shape matching using Laplacian eigenfunctions and unsupervised point registration, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587538
URL : https://hal.archives-ouvertes.fr/inria-00590251

S. Moss and E. Hancock, Image registration with shape mixtures [33] A. Myronenko and X. Song. Point-Set Registration: Coherent Point Drift, Image Analysis and Processing, pp.172-1792262, 1997.

A. Myronenko, X. Song, and M. Carreira-perpinan, Non-rigid point set registration: Coherent point drift, Advances in Neural Information Processing Systems, pp.1009-1016, 2007.

A. Rangarajan, H. Chui, E. Mjolsness, S. Pappu, L. Davachi et al., A robust point-matching algorithm for autoradiograph alignment, Medical Image Analysis, vol.1, issue.4, pp.379-398, 1997.
DOI : 10.1016/S1361-8415(97)85008-6

M. Steven and . Robbins, Anatomical standardization of the human brain in euclidean 3-space and on the cortical 2-manifold, 2004.

A. S. Roy, A. Gopinath, and A. Rangarajan, Deformable Density Matching for 3D Non-rigid Registration of Shapes, Medical Image Computind anf Computer Assisted Intervention, vol.10, pp.942-951, 2007.
DOI : 10.1007/978-3-540-75757-3_114

R. Sandhu, S. Dambreville, and A. Tannenbaum, Point Set Registration via Particle Filtering and Stochastic Dynamics, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.8, 2009.
DOI : 10.1109/TPAMI.2009.142

B. Schölkopf, R. Herbrich, and A. J. Smola, A Generalized Representer Theorem, Annual Conference on Computational Learning Theory, pp.416-426, 2001.
DOI : 10.1007/3-540-44581-1_27

A. J. Scott and M. J. Symons, Clustering Methods Based on Likelihood Ratio Criteria, Biometrics, vol.27, issue.2, pp.387-397, 1971.
DOI : 10.2307/2529003

G. L. Scott and H. C. Longuet-higgins, An Algorithm for Associating the Features of Two Images, Proceedings of the Royal Society B: Biological Sciences, vol.244, issue.1309, pp.21-26, 1991.
DOI : 10.1098/rspb.1991.0045

L. S. Shapiro and J. M. Brady, Feature-based correspondence: an eigenvector approach, Image and Vision Computing, vol.10, issue.5, pp.283-288, 1992.
DOI : 10.1016/0262-8856(92)90043-3

L. Shen, H. Huang, F. Makedon, and A. J. Saykin, Efficient Registration of 3D SPHARM Surfaces, Fourth Canadian Conference on Computer and Robot Vision (CRV '07), pp.81-88, 2007.
DOI : 10.1109/CRV.2007.26

T. Sidlofov, Existence and uniqueness of minimization problems with Fourier based stabilizers, Compstat, 2004.

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

T. Tang and A. Chung, Non-rigid Image Registration Using Graph-cuts, Medical Image Computing and Computer-Assisted Intervention, 2007.
DOI : 10.1007/978-3-540-75757-3_111

J. Thirion, Image matching as a diffusion process: an analogy with Maxwell's demons, Medical Image Analysis, vol.2, issue.3, pp.243-260, 1998.
DOI : 10.1016/S1361-8415(98)80022-4

Y. Tsin and T. Kanade, A Correlation-Based Approach to Robust Point Set Registration, European conference on computer vision, pp.558-569, 2004.
DOI : 10.1007/978-3-540-24672-5_44

M. Vaillant and J. Glaunès, Surface Matching via Currents, Proceedings of Information Processing in Medical Imaging, pp.381-392, 2005.
DOI : 10.1007/11505730_32
URL : https://hal.archives-ouvertes.fr/hal-00263652

F. Wang, B. Vemuri, and T. Syeda-mahmood, Generalized L2-Divergence and Its Application to Shape Alignment, IEEE Information Processing in Medical Imaging, pp.227-238, 2009.
DOI : 10.1007/978-3-540-75757-3_32

F. Wang, B. C. Vemuri, and A. Rangarajan, Groupwise point pattern registration using a novel CDF-based Jensen-Shannon divergence, IEEE conference on Computer Vision and Pattern Recognition, pp.1283-1288, 2006.

H. Wang, D. Mirota, and G. D. Hager, A Generalized Kernel Consensus-Based Robust Estimator, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.1, pp.178-184, 2010.
DOI : 10.1109/TPAMI.2009.148

M. W. Wells and I. , Statistical approaches to feature-based object recognition, International Journal of Computer Vision, vol.21, issue.1/2, pp.63-98, 1997.
DOI : 10.1023/A:1007923522710

H. Wendland, Scattered Data Approximation, Cambridge Monographs on Applied and Computational Mathematics, 2005.
DOI : 10.1017/CBO9780511617539

B. T. Yeo, M. R. Sabuncu, T. Vercauteren, N. Ayache, B. Fischl et al., Spherical Demons: Fast Diffeomorphic Landmark-Free Surface Registration, IEEE Transactions on Medical Imaging, vol.29, issue.3, pp.650-668, 2010.
DOI : 10.1109/TMI.2009.2030797
URL : https://hal.archives-ouvertes.fr/inria-00616102

A. L. Yuille and N. M. Grzywacz, A mathematical analysis of the motion coherence theory, International Journal of Computer Vision, vol.213, issue.2, pp.155-175, 1989.
DOI : 10.1007/BF00126430

G. Zou, J. Hua, and O. Muzik, Non-rigid Surface Registration Using Spherical Thin-Plate Splines, Medical Image Computing and Computer-Assisted Intervention, pp.367-374, 2007.
DOI : 10.1007/978-3-540-75757-3_45