Image distance functions for manifold learning

Image and Vision Computing

Volumn 25, Issue 3, 2007, Pages 365-373

  Souvenir, Richard ^a   Pless, Robert ^a  

^a WASHINGTON UNIVERSITY IN ST LOUIS   (United States)

Author keywords

Isomap; Manifolds; Non parametric registration

Indexed keywords

CONFORMAL MAPPING; DATA STRUCTURES; IMAGE ANALYSIS; LINEAR SYSTEMS; PARAMETER ESTIMATION; PRINCIPAL COMPONENT ANALYSIS;

IMAGE DISTANCE FUNCTIONS; ISOMAP; MANIFOLD LEARNING; NON PARAMETRIC REGISTRATION;

LEARNING SYSTEMS;

EID: 33845335824     PISSN: 02628856     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.imavis.2006.01.016     Document Type: Article

References (14)

1. M. Belkin, P. Niyogi, Laplacian eigenmaps and spectral techniques for embedding and clustering, in: Advances in Neural Information Processing Systems, 2002.
2. Bengio Y., Paiement J., Vincent P., Delalleau O., Le Roux N., and Ouimet M. Out-of-sample extensions for lle, isomap, mds, eigenmaps, and spectral clustering. In: Thrun S., Saul L., and Schölkopf B. (Eds). Advances in Neural Information Processing Systems vol. 16 (2004), MIT Press, Cambridge, MA
3. Borg I., and Groenen P. Modern Multidimensional Scaling: Theory and Applications (1997), Springer, Berlin
4. Donoho D.L., and Grimes A C. Hessian eigenmaps: locally linear embedding techniques for high-dimensional data. Proceedings of the National Academy of Science 100 (2003) 5591-5596
5. Grenander U. Elements of Pattern Theory (MD, 1996), Johns Hopkins University Press, Baltimore
6. I.S. Lim, P.H. Ciechomski, S. Sarni, D. Thalmann, Planar arrangement of high-dimensional biomedical data sets by isomap coordinates, in: Proceedings of the 16th IEEE Symposium on Computer-Based Medical Systems (CBMS 2003), New York, 2003.
7. R. Pless, I. Simon, Using thousands of images of an object, in: CVPRIP, 2002.
8. Roweis S.T., and Saul L.K. Nonlinear dimensionality reduction by locally linear embedding. Science 290 5500 (2000) 2323-2326
9. Y.W. Teh, S. Roweis, Automatic alignment of local representations, in: Advances in Neural Information Processing Systems, vol. 15, 2003.
10. Tenenbaum J.B., de Silva V., and Langford J.C. A global geometric framework for nonlinear dimensionality reduction. Science 290 5500 (2000) 2319-2323
11. Thompson D. On Growth and Form (1917), Cambridge University Press, Cambridge
12. Trouve A. Diffeomorphism groups and pattern matching in image analysis. International Journal of Computer Vision 28 (1998) 213-221
13. A. Trouve, L. Younes, Local analysis of a shape manifold, Technical Report 2002-2003, Laboratoire d'Analyse, Geometric et Applications, CNRS, Universite Paris, 2002.
14. K.Q. Weinberger, L.K. Saul, Unsupervised learning of image manifolds by semidefinite programming, in: Computer Vision and Pattern Recognition, 2004.