Tracking People with Networks of Heterogeneous Sensors

This paper describes the theory and implementation of a system of distributed sensors which work together to identify and track moving people using different sensing modalities in real time. Algorithms for detecting people using cameras and laser scanners are presented. A Kalman Filter is used to fuse the information gathered from the various sensors. Access to information from different kinds of sensors makes each individual sensor more powerful. Results of these techniques to tracking of a person moving in a typical office environment are presented.

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