Object tracking in the presence of occlusions via a camera network
Proceedings of the 6th international conference on Information processing in sensor networks
On the optimality of motion-based particle filtering
IEEE Transactions on Circuits and Systems for Video Technology
Path recovery of a disappearing target in a large network of cameras
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
Object tracking in the presence of occlusions using multiple cameras: A sensor network approach
ACM Transactions on Sensor Networks (TOSN)
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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 on-line algorithm for efficient, approximate inference and we demonstrate it to be accurate in an office environment.