37 search results - page 2 / 8 » Dynamical Binary Latent Variable Models for 3D Human Pose Tr... |
NIPS
2007
13 years 6 months ago
2007
Reliably recovering 3D human pose from monocular video requires models that bias the estimates towards typical human poses and motions. We construct priors for people tracking usi...
ICCV
2005
IEEE
13 years 10 months ago
2005
IEEE
We advocate the use of Scaled Gaussian Process Latent Variable Models (SGPLVM) to learn prior models of 3D human pose for 3D people tracking. The SGPLVM simultaneously optimizes a...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Current approaches to pose estimation and tracking can be classified into two categories: generative and discriminative. While generative approaches can accurately determine human...
ICIP
2007
IEEE
14 years 6 months ago
2007
IEEE
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...
ICASSP
2009
IEEE
13 years 11 months ago
2009
IEEE
This paper presents a multi-view articulated human motion tracking framework using particle filter with manifold learning through Gaussian process latent variable model. The dime...