Estimation of Space-Varying Covariance Matrices

This paper considers the representation of human trajectories in video signals. These trajectories are modeled by switched dynamical models, based on motion fields that drive the pedestrian during consecutive time intervals. This paper addresses the estimation of uncertainty in trajectory generation by using space-varying covariance matrices estimated from the video data. Experimental results show that the proposed model outperforms previous methods, based on static and isotropic covariance matrices.