148 search results - page 25 / 30 » Riemannian Manifold Learning for Nonlinear Dimensionality Re... |
IVC
2007
13 years 7 months ago
2007
- Canonical correlation analysis (CCA) is a major linear subspace approach to dimensionality reduction and has been applied to image processing, pose estimation and other fields. H...
ACMACE
2008
ACM
13 years 9 months ago
2008
ACM
Dimensionality reduction is a statistical tool commonly used to map high-dimensional data into lower a dimensionality. The transformed data is typically more suitable for regressi...
CVPR
2003
IEEE
14 years 9 months ago
2003
IEEE
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
CORR
2011
Springer
13 years 2 months ago
2011
Springer
—We consider the problem of positioning a cloud of points in the Euclidean space Rd , from noisy measurements of a subset of pairwise distances. This task has applications in var...