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.
展开▼