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...
We propose a person-dependent, manifold-based approach for modeling and tracking rigid and nonrigid 3D facial deformations from a monocular video sequence. The rigid and nonrigid ...
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...
Filtering based algorithms have become popular in tracking human body pose. Such algorithms can suffer the curse of dimensionality due to the high dimensionality of the pose state ...
Rui Li, Ming-Hsuan Yang, Stan Sclaroff, Tai-Peng T...
We explore an approach to 3D people tracking with learned motion models and deterministic optimization. The tracking problem is formulated as the minimization of a differentiable ...