88 search results - page 6 / 18 » Distance Preserving Dimension Reduction for Manifold Learnin... |
BMVC
2010
13 years 6 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...
TSP
2010
13 years 3 months ago
2010
In this paper, we present multiple novel applications for local intrinsic dimension estimation. There has been much work done on estimating the global dimension of a data set, typi...
CVPR
2007
IEEE
14 years 2 months ago
2007
IEEE
Although it is usually assumed in many pattern recognition problems that different patterns are distinguishable, some patterns may have inseparable overlap. For example, some faci...
ICCV
2009
IEEE
15 years 1 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...
ICASSP
2007
IEEE
14 years 2 months ago
2007
IEEE
A novel method for robust super-resolution offace images is proposed in this paper. Face super-resolution is a particular interest in video surveillance where face images have typ...