148 search results - page 18 / 30 » Riemannian Manifold Learning for Nonlinear Dimensionality Re... |
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
Inferring 3D body pose as well as viewpoint from a single silhouette image is a challenging problem. We present a new generative model to represent shape deformations according to...
CVPR
2008
IEEE
13 years 7 months ago
2008
IEEE
Learning a robust projection with a small number of training samples is still a challenging problem in face recognition, especially when the unseen faces have extreme variation in...
ECCV
2004
Springer
14 years 9 months ago
2004
Springer
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
ECML
2005
Springer
14 years 1 months ago
2005
Springer
Spectral methods for embedding graphs and immersing data manifolds in low-dimensional speaces are notoriously unstable due to insufficient and/or numberically ill-conditioned con...