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CRV
2008
IEEE
295views Robotics» more  CRV 2008»
12 years 6 months ago
3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
Kooksang Moon, Vladimir Pavlovic
ICIP
2007
IEEE
13 years 1 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
CVPR
2010
IEEE
12 years 8 months ago
Dynamical Binary Latent Variable Models for 3D Human Pose Tracking
We introduce a new class of probabilistic latent variable model called the Implicit Mixture of Conditional Restricted Boltzmann Machines (imCRBM) for use in human pose tracking. K...
Graham Taylor, Leonid Sigal, David Fleet, Geoffrey...
ECCV
2004
Springer
13 years 1 months ago
3D Human Body Tracking Using Deterministic Temporal Motion Models
Abstract. There has been much effort invested in increasing the robustness of human body tracking by incorporating motion models. Most approaches are probabilistic in nature and se...
Raquel Urtasun, Pascal Fua
IBPRIA
2005
Springer
12 years 5 months ago
A 3D Dynamic Model of Human Actions for Probabilistic Image Tracking
Abstract. In this paper we present a method suitable to be used for human tracking as a temporal prior in a particle ļ¬ltering framework such as CONDENSATION [5]. This method is f...
Ignasi Rius, Daniel Rowe, Jordi Gonzàlez, F...
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