Bayesian Propagation for Perceiving Moving Objects

In this paper we address the issue of how form and motion can be integrated in order to provide suitable information to attentively track multiple moving objects. Such integration is designed in a Bayesian framework, and a Belief Propagation technique is exploited to perform coherent form/motion labelling of regions of the observed scene. Experiments on both synthetic and real data are presented and discussed.