154 search results - page 2 / 31 » Incremental Nonlinear Dimensionality Reduction by Manifold L... |
BMVC
2010
13 years 4 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
CVPR
2006
IEEE
14 years 8 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...
CVPR
2008
IEEE
14 years 8 months ago
2008
IEEE
We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...
SDM
2004
SIAM
13 years 7 months ago
2004
SIAM
There has been a renewed interest in understanding the structure of high dimensional data set based on manifold learning. Examples include ISOMAP [25], LLE [20] and Laplacian Eige...
AMDO
2006
Springer
13 years 10 months ago
2006
Springer
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...