Algorithms for cooperative multisensor surveillance

Robert T. Collins, Alan J. Lipton, Hironobu Fujiyoshi, Takeo Kanade

Research output: Contribution to journalArticlepeer-review

515 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1456-1477
Number of pages22
JournalProceedings of the IEEE
Issue number10
StatePublished - 2001

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering


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