207 search results - page 2 / 42 » Regularized Principal Manifolds |
ICIP
2010
IEEE
13 years 3 months ago
2010
IEEE
Transformation manifolds are quite attractive for image analysis applications that require transformation invariance properties. The geometric structure of a transformation manifo...
ICASSP
2010
IEEE
13 years 5 months ago
2010
IEEE
The characterization of signals and images in manifolds often lead to efficient dimensionality reduction algorithms based on manifold distance computation for analysis or classi...
VLSM
2005
Springer
13 years 10 months ago
2005
Springer
The need to regularize tensor fields arise recently in various applications. We treat in this paper tensors that belong to matrix Lie groups. We formulate the problem of these SO(...
ICCV
1999
IEEE
13 years 9 months ago
1999
IEEE
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Three techniques: Principal Component Analy...
ICCV
2009
IEEE
14 years 10 months ago
2009
IEEE
We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...