Tracking of moving objects with multiple models using Gaussian mixtures

This paper addresses the problem of tracking of objects with complex shape or motion dynamics. The approach followed relies on multiple models based on Gaussian mixtures and hidden Markov models. A tracking algorithm derived from nonlinear filtering is presented and illustrated in two situations. In the first, two points moving independently along a line are tracked, only one being observed at each time. In the second, two-dimensional objects are tracked, under severe shape deformations. Unlike other multi-model approaches, the proposed method relies on parametric techniques providing an efficient tool to update shape and motion estimates.