S. Dambreville, Y. Rathi, and A. Tannenbaum, Statistical shape analysis using kernel pca, IS&T/SPIE Symposium on Electronic Imaging, 2006.

P. Arias, G. Randall, and G. Sapiro, Connecting the Out-of-Sample and Pre-Image Problems in Kernel Methods, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383038

J. T. Kwok and I. W. Tsang, The Pre-Image Problem in Kernel Methods, IEEE Transactions on Neural Networks, vol.15, issue.6, pp.1517-1525, 2004.
DOI : 10.1109/TNN.2004.837781

M. A. Carreira-perpiñan and Z. Lu, The Laplacian Eigenmaps Latent Variable Model, JMLR W&P, vol.2, pp.59-66, 2007.

S. Roweis and L. Saul, Nonlinear Dimensionality Reduction by Locally Linear Embedding, Science, vol.290, issue.5500, pp.2323-2326, 2000.
DOI : 10.1126/science.290.5500.2323

J. B. Tenenbaum, V. De-silva, and J. C. Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction, Science, vol.290, issue.5500, pp.2319-2323, 2000.
DOI : 10.1126/science.290.5500.2319

M. Belkin and P. Niyogi, Laplacian Eigenmaps for Dimensionality Reduction and Data Representation, Neural Computation, vol.15, issue.6, pp.1373-1396, 2003.
DOI : 10.1126/science.290.5500.2319

R. Coifman, S. Lafon, A. Lee, M. Maggioni, B. Nadler et al., Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps, Proceedings of the National Academy of Sciences, vol.102, issue.21, pp.7426-7431, 2005.
DOI : 10.1073/pnas.0500334102

M. Hein, J. Y. Audibert, and U. Von-luxburg, From Graphs to Manifolds ??? Weak and Strong Pointwise Consistency of Graph Laplacians, ArXiv Preprint Journal of Machine Learning Research, p.forthcoming, 2006.
DOI : 10.1007/11503415_32

S. Lafon, Y. Keller, and R. R. Coifman, Data Fusion and Multicue Data Matching by Diffusion Maps, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.11, pp.1784-1797, 2006.
DOI : 10.1109/TPAMI.2006.223

M. Leventon, E. Grimson, and O. Faugeras, Statistical shape influence in geodesic active contours, IEEE Conference on Computer Vision and Pattern Recognition, pp.316-323, 2000.

Z. Lu, M. Carreira-perpinan, and C. Sminchisescu, People tracking with the laplacian eigenmaps latent variable model, Advances in Neural Information Processing Systems, pp.1705-1712, 2008.

X. Pennec, Intrinsic Statistics on Riemannian Manifolds: Basic Tools for Geometric Measurements, Journal of Mathematical Imaging and Vision, vol.20, issue.10, pp.127-154, 2004.
DOI : 10.1007/s10851-006-6228-4
URL : https://hal.archives-ouvertes.fr/inria-00614994

B. Davis, P. Fletcher, E. Bullitt, and S. Joshi, Population shape regression from random design data, 2007.

H. Karcher, Riemannian center of mass and mollifier smoothing, Communications on Pure and Applied Mathematics, vol.3, issue.5, pp.509-541, 1977.
DOI : 10.1002/cpa.3160300502

P. Etyngier, F. Segonne, and R. Keriven, Shape Priors using Manifold Learning Techniques, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4409040

S. Lafon and A. B. Lee, Diffusion maps and coarse-graining: a unified framework for dimensionality reduction, graph partitioning, and data set parameterization. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.28, issue.9, pp.1393-1403, 2006.

Y. Bengio, J. F. Paiement, P. Vincent, O. Delalleau, L. Roux et al., Out-ofsample extensions for lle, isomap, mds, eigenmaps, and spectral clustering, Advances in Neural Information Processing Systems 16, 2004.

C. T. Baker and C. T. Baker, Numerical analysis of volterra functional and integral equations The state of the art in numerical analysis, pp.193-222, 1996.

P. Etyngier, R. Keriven, and F. Segonne, Projection onto a Shape Manifold for Image Segmentation with Prior, 2007 IEEE International Conference on Image Processing, 2007.
DOI : 10.1109/ICIP.2007.4380029

G. Charpiat, O. Faugeras, and R. Keriven, Approximations of Shape Metrics and Application to Shape Warping and Empirical Shape Statistics, Foundations of Computational Mathematics, vol.5, issue.1, pp.1-58, 2005.
DOI : 10.1007/s10208-003-0094-x
URL : https://hal.archives-ouvertes.fr/inria-00071766

J. Solem, Geodesic curves for analysis of continuous implicit shapes, International Conference on Pattern Recognition, pp.43-46, 2006.

M. Rousson and N. Paragios, Shape Priors for Level Set Representations, European Conference on Computer Vision, pp.78-92, 2002.
DOI : 10.1007/3-540-47967-8_6