This paper proposes a novel visualization approach, which can depict the variations between different human motion data. This is achieved by representing the time dimension of eac...
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...
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Abstract. Due to its great ability of conquering clutters, which is especially useful for high-dimensional tracking problems, particle filter becomes popular in the visual trackin...
Estimating mode (walking/running/standing) and phases of human locomotion is important for video understanding. We present a new ”tracking as recognition” approach. A hierarch...