Robert T. Collins, Alan J. Lipton, Hironobu Fujiyoshi and Takeo Kanade,
"Algorithms for Cooperative Multisensor Surveillance,"
Proceedings of the IEEE, Vol 89(10), Oct 2001, pp.1456-1477.
The Video Surveillance and Monitoring (VSAM) team at Carnegie Mellon
University (CMU) has developed an end-to-end, multi-camera
surveillance system that allows a single human operator to monitor
activities in a cluttered environment using a distributed network of
active video sensors. Video understanding algorithms have been
developed to automatically detect people and vehicles, seamlessly
track them using a network of cooperating active sensors, determine
their 3D locations with respect to a geospatial site model, and
present this information to a human operator who controls the system
through a graphical user interface. The goal is to automatically
collect and disseminate real-time information to improve the
situational awareness of security providers and decision makers. The
feasibility of real-time video surveillance has been demonstrated
within a multi-camera testbed system developed on the campus of CMU.
This paper presents an overview of the issues and algorithms involved
in creating this semi-autonomous, multi-camera surveillance system.
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full paper (624217 bytes, pdf file).