154 search results - page 25 / 31 » Incremental Nonlinear Dimensionality Reduction by Manifold L... |
ROBOCUP
2004
Springer
15 years 5 months ago
2004
Springer
Abstract. This paper proposes a new algorithm for the automatic segmentation of motion data from a humanoid soccer playing robot that allows feedforward neural networks to generali...
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ICCV
2007
IEEE
16 years 1 months ago
2007
IEEE
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
IVC
2007
14 years 11 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
15 years 1 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
16 years 1 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...