11 search results - page 2 / 3 » Monocular Tracking 3D People By Gaussian Process Spatio-Temp... |
AVSS
2006
IEEE
13 years 10 months ago
2006
IEEE
Extracting meaningful 3D human motion information from video sequences is of interest for applications like intelligent humancomputer interfaces, biometrics, video browsing and ind...
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...
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...
HUMO
2007
Springer
13 years 10 months ago
2007
Springer
Abstract. Learned, activity-specific motion models are useful for human pose and motion estimation. Nevertheless, while the use of activityspecific models simplifies monocular t...
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...