29 search results - page 3 / 6 » Context and observation driven latent variable model for hum... |
CVPR
2010
IEEE
14 years 2 months ago
2010
IEEE
Detecting objects in cluttered scenes and estimating articulated human body parts are two challenging problems in computer vision. The difficulty is particularly pronounced in ac...
PAMI
2008
13 years 6 months ago
2008
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
CVPR
2004
IEEE
14 years 8 months ago
2004
IEEE
This paper addresses the problem of estimating human body pose in static images. This problem is challenging due to the high dimensional state space of body poses, the presence of...
ICASSP
2009
IEEE
14 years 1 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...
ICCV
2005
IEEE
14 years 8 months ago
2005
IEEE
Tree structured models have been widely used for determining the pose of a human body, from either 2D or 3D data. While such models can effectively represent the kinematic constra...