Online multicamera tracking with a switching state-space model

Abstract

The paper presents a novel method for online tracking of multiple objects with non-overlapping cameras. The method is based on a generative model defining probabilistic dependencies between observations, the underlying color properties of objects and their dynamics. It allows for a full Bayesian inference of trajectories. We developed an online algorithm for efficient, approximate inference and we demonstrate it to be accurate in an office environment.