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CVPR
2009
IEEE
13 years 8 months ago
Switching Gaussian Process Dynamic Models for simultaneous composite motion tracking and recognition
Traditional dynamical systems used for motion tracking cannot effectively handle high dimensionality of the motion states and composite dynamics. In this paper, to address both is...
Jixu Chen, Minyoung Kim, Yu Wang, Qiang Ji
IPSN
2010
Springer
13 years 6 months ago
Collaborative signal processing for action recognition in body sensor networks: a distributed classification algorithm using mot
Body sensor networks are emerging as a promising platform for remote human monitoring. With the aim of extracting bio-kinematic parameters from distributed body-worn sensors, thes...
Hassan Ghasemzadeh, Vitali Loseu, Roozbeh Jafari
ICPR
2008
IEEE
13 years 11 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
CVPR
2006
IEEE
14 years 6 months ago
3D People Tracking with Gaussian Process Dynamical Models
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
Raquel Urtasun, David J. Fleet, Pascal Fua