We present a multi-camera system based on Bayesian modality fusion to track multiple people in an indoor environment. Bayesian networks are used to combine multiple modalities for matching subjects between consecutive imge frames and between multipl
In this paper, we address the issue of tracking moving objects in an environment covered by multiple uncalibrated cameras with overlapping fields of view, typical of most surveillance setups. In such a scenario, it is essential to establish correspo
We present an automatic, real-time human tracking and observation system. Robustness and speed are the two major bottlenecks of the existing approaches. We improve upon the robustness and speed of the current state-of-art by integrating a mean-shift
