A probabilistic shape filter for online contour tracking

Online contour-based tracking is considered through the estimation perspective. We propose a recursive dynamic filtering solution to the tracking problem. The state of the target is described by a pose state which represents the ensemble movement and a shape state which represents the local deformations. The shape state of the filter is described implicitly by a probability field with prediction and correction mechanisms expressed accordingly. The filtering procedure decouples the pose and shape estimation. Experiments conducted with objective measures of quality demonstrate improved tracking.