We present a novel approach to tracking 2D human motion in uncalibrated monocular videos. Human motion usually exhibits timevarying patterns, and we propose to use locally learnt ...
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 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...
— A new approach to the 3D human motion tracking problem is proposed, which combines several particle filters with a physical simulation of a flexible body model. The flexible...
Our paper addresses the problem of enforcing constraints in human body tracking. A projection technique is derived to impose kinematic constraints on independent multi-body motion...