468 search results - page 44 / 94 » Riemannian Manifold Learning |
101
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ECCV
2002
Springer
16 years 1 months ago
2002
Springer
Abstract. In many vision problems, the observed data lies in a nonlinear manifold in a high-dimensional space. This paper presents a generic modelling scheme to characterize the no...
113
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ESANN
2006
15 years 1 months ago
2006
We present an extension to a recent method for learning of nonlinear manifolds, which allows to incorporate general cost functions. We focus on the -insensitive loss and visually d...
CVPR
2006
IEEE
16 years 1 months ago
2006
IEEE
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
IJCV
2007
14 years 11 months ago
2007
The parameter space for the ellipses in a two dimensional image is a five dimensional manifold, where each point of the manifold corresponds to an ellipse in the image. The parame...
TMI
2008
14 years 11 months ago
2008
Abstract--This paper investigates the performance of a new multivariate method for tensor-based morphometry (TBM). Statistics on Riemannian manifolds are developed that exploit the...