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ICPR
2008
IEEE
15 years 4 months ago
Tracking human body by using particle filter Gaussian process Markov-switching model
The goal of this article is to present an effective and robust tracking algorithm for nonlinear feet motion by deploying particle filter integrated with Gaussian process latent v...
Jing Wang, Hong Man, Yafeng Yin
ICIP
2007
IEEE
15 years 11 months ago
Monocular Tracking 3D People By Gaussian Process Spatio-Temporal Variable Model
Tracking 3D people from monocular video is often poorly constrained. To mitigate this problem, prior knowledge should be exploited. In this paper, the Gaussian process spatio-temp...
Junbiao Pang, Laiyun Qing, Qingming Huang, Shuqian...
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ICIP
2007
IEEE
15 years 11 months ago
3D Human Motion Tracking using Manifold Learning
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Feng Guo, Gang Qian
ICML
2008
IEEE
15 years 10 months ago
Topologically-constrained latent variable models
In dimensionality reduction approaches, the data are typically embedded in a Euclidean latent space. However for some data sets this is inappropriate. For example, in human motion...
Raquel Urtasun, David J. Fleet, Andreas Geiger, Jo...
ACCV
2010
Springer
14 years 4 months ago
Latent Gaussian Mixture Regression for Human Pose Estimation
Discriminative approaches for human pose estimation model the functional mapping, or conditional distribution, between image features and 3D pose. Learning such multi-modal models ...
Yan Tian, Leonid Sigal, Hernán Badino, Fern...