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» Learning Switching Linear Models of Human Motion
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AMDO
2006
Springer
13 years 11 months ago
Monocular Tracking with a Mixture of View-Dependent Learned Models
This paper considers the problem of monocular human body tracking using learned models. We propose to learn the joint probability distribution of appearance and body pose using a m...
Tobias Jaeggli, Esther Koller-Meier, Luc J. Van Go...
ICML
2007
IEEE
14 years 8 months ago
Multifactor Gaussian process models for style-content separation
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
ICML
2007
IEEE
14 years 8 months ago
Hierarchical Gaussian process latent variable models
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
Neil D. Lawrence, Andrew J. Moore
ICCV
2003
IEEE
14 years 1 months ago
Tracking Articulated Hand Motion with Eigen Dynamics Analysis
This paper introduces the concept of eigen-dynamics and proposes an eigen dynamics analysis (EDA) method to learn the dynamics of natural hand motion from labelled sets of motion ...
Hanning Zhou, Thomas S. Huang
CVPR
2009
IEEE
15 years 3 months ago
Learning Visual Flows: A Lie Algebraic Approach
We present a novel method for modeling dynamic visual phenomena, which consists of two key aspects. First, the in- tegral motion of constituent elements in a dynamic scene is ca...
Dahua Lin, W. Eric L. Grimson, John W. Fisher III