S. Agarwal, J. Lim, L. Zelnik-manor, P. Perona, D. Kriegman et al., Beyond Pairwise Clustering, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
DOI : 10.1109/CVPR.2005.89

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

M. Belkin and P. Niyogi, Laplacian eigenmaps and spectral techniques for embedding and clustering, NIPS'01, 2001.

M. Brand, Shadow puppetry, Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999.
DOI : 10.1109/ICCV.1999.790422

A. M. Bronstein, M. M. Bronstein, and R. Kimmel, Generalized multidimensional scaling: A framework for isometry-invariant partial surface matching, Proceedings of the National Academy of Sciences, vol.103, issue.5, pp.1168-1172, 2006.
DOI : 10.1073/pnas.0508601103

G. Brostow, I. Essa, D. Steedly, and V. Kwatra, Novel Skeletal Representation for Articulated Creatures, ECCV'04, 2004.
DOI : 10.1007/978-3-540-24672-5_6

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

C. Chu, O. C. Jenkins, and M. J. Mataric, Markerless kinematic model and motion capture from volume sequences, CVPR'03, 2003.

A. P. Dempster, N. M. Laird, and D. B. Rubin, Maximum likelihood from incomplete data via the EM algorithm, J. Royal Stat. Soc, vol.39, pp.1-38, 1977.

D. L. Donoho and C. Grimes, Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data, Proceedings of the National Academy of Sciences, pp.5591-5596, 2003.
DOI : 10.1073/pnas.1031596100

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC156245

A. Elgammal and C. Lee, Inferring 3D body pose from silhouettes using activity manifold learning, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., 2004.
DOI : 10.1109/CVPR.2004.1315230

URL : http://athos.rutgers.edu/~elgammal/pub/learn3Dpose_CVPR04.pdf

D. Gavrila and L. Davis, 3D model-based tracking of humans in action: a multi-view approach, CVPR'96, 1996.

K. Grauman, G. Shakhnarovich, and T. Darrell, Inferring 3D structure with a statistical image-based shape model, Proceedings Ninth IEEE International Conference on Computer Vision, 2003.
DOI : 10.1109/ICCV.2003.1238408

D. Hogg, Model-based vision: a program to see a walking person, Image and Vision Computing, 1983.
DOI : 10.1016/0262-8856(83)90003-3

V. Jain and H. Zhang, Robust 3d shape correspondence in the spectral domain, SMI'06, 2006.

O. Jenkins and M. Mataric, A spatio-temporal extension to Isomap nonlinear dimension reduction, Twenty-first international conference on Machine learning , ICML '04, 2004.
DOI : 10.1145/1015330.1015357

B. Lévy, Laplace-Beltrami Eigenfunctions Towards an Algorithm That "Understands" Geometry, IEEE International Conference on Shape Modeling and Applications 2006 (SMI'06), 2006.
DOI : 10.1109/SMI.2006.21

R. Lin, C. Liu, M. Yang, N. Ahuja, and S. Levinson, Learning Nonlinear Manifolds from Time Series, ECCV'06, 2006.
DOI : 10.1007/978-3-540-24671-8_48

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

T. Moeslund, A. Hilton, and V. Krüger, A survey of advances in vision-based human motion capture and analysis, Computer Vision and Image Understanding, vol.104, issue.2-3, 2006.
DOI : 10.1016/j.cviu.2006.08.002

A. Ng, M. Jordan, and Y. Weiss, On spectral clustering: Analysis and an algorithm, NIPS'01, 2001.

G. Rosman, A. Bronstein, M. Bronstein, and R. Kimmel, Manifold analysis by topologically constrained isometric embedding, International Journal of Applied Mathematics and Computer Sciences, vol.1, issue.3, pp.117-123, 2004.
DOI : 10.1007/978-1-4020-6693-1_10

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

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

URL : http://astro.temple.edu/~msobel/courses_files/saulmds.pdf

J. Shi and J. Malik, Normalized cuts and image segmentation, PAMI, vol.22, issue.8, pp.888-905, 2000.

A. Sundaresan and R. Chellappa, Segmentation and Probalistic Registration of Articulated Body Models, ICPR'06, 2006.

J. B. Tenenbaum, V. D. Silva, and J. C. Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction, Science, vol.290, issue.5500, pp.2902319-2323, 2000.
DOI : 10.1126/science.290.5500.2319

K. Zhou, J. Huang, J. Snyder, X. Liu, H. Bao et al., Large mesh deformation using the volumetric graph Laplacian, ACM Transactions on Graphics, vol.24, issue.3, pp.496-503, 2005.
DOI : 10.1145/1073204.1073219