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» Dimensionality Reduction and Clustering on Statistical Manif...
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NIPS
2003
13 years 7 months ago
Optimal Manifold Representation of Data: An Information Theoretic Approach
We introduce an information theoretic method for nonparametric, nonlinear dimensionality reduction, based on the infinite cluster limit of rate distortion theory. By constraining...
Denis V. Chigirev, William Bialek
AMDO
2006
Springer
13 years 9 months ago
Human Motion Synthesis by Motion Manifold Learning and Motion Primitive Segmentation
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
Chan-Su Lee, Ahmed M. Elgammal
SAC
2005
ACM
13 years 11 months ago
Estimating manifold dimension by inversion error
Video and image datasets can often be described by a small number of parameters, even though each image usually consists of hundreds or thousands of pixels. This observation is of...
Shawn Martin, Alex Bäcker
TSP
2010
13 years 9 days ago
On local intrinsic dimension estimation and its applications
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...
Kevin M. Carter, Raviv Raich, Alfred O. Hero
CVPR
2007
IEEE
14 years 7 months ago
Segmenting Motions of Different Types by Unsupervised Manifold Clustering
We propose a novel algorithm for segmenting multiple motions of different types from point correspondences in multiple affine or perspective views. Since point trajectories associ...
Alvina Goh, René Vidal