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...
This paper addresses the reconstruction of 3 0 human body models fram Z D video sequences. Considering that the input frames are already segmented, the proposed technique consists...
Much of the research on video-based human motion capture assumes the body shape is known a priori and is represented coarsely (e.g. using cylinders or superquadrics to model limbs...
Alexandru O. Balan, Leonid Sigal, Michael J. Black...
Estimating human body poses in static images is important for many image understanding applications including semantic content extraction and image database query and retrieval. Th...
We introduce a generic and efficient method for 2D and 3D shape estimation via density Þelds. Our method models shape as a density map and uses the notion of density to Þt a mod...