The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

The Video Surveillance and Monitoring (VSAM) team at Carnegie Mellon University (CMU) has developed an end-to-end, multicamera 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 three-dimensional 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 multicamera testbed system developed on the campus of CMU. This paper presents an overview of the issues and algorithms involved in creating this semiautonomous, multicamera surveillance system.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Lab(s) / Group(s): Video Surveillance and Monitoring and People Image Analysis Consortium

Associated Project(s): Video Surveillance and Monitoring

Text Reference

Robert Collins, Alan Lipton, Hironobu Fujiyoshi, and Takeo Kanade, "Algorithms for cooperative multisensor surveillance," Proceedings of the IEEE, Vol. 89, No. 10, October, 2001, pp. 1456 - 1477.

BibTeX Reference

@article{Collins_2001_4127,
   author = "Robert Collins and Alan Lipton and Hironobu Fujiyoshi and Takeo Kanade",
   title = "Algorithms for cooperative multisensor surveillance",
   journal = "Proceedings of the IEEE",
   pages = "1456 - 1477",
   month = "October",
   year = "2001",
   volume = "89",
   number = "10",
}

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