Algorithms for cooperative multisensor surveillance

  • Collins R
  • Lipton A
  • Fujiyoshi H
 et al. 
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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

Author-supplied keywords

  • Active vision
  • Cooperative systems
  • Geolocation
  • Multisensor systems
  • Site security monitoring
  • User interfaces
  • Video surveillance. © 2001 ieee

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  • Robert T. Collins

  • Alan J. Lipton

  • Hironobu Fujiyoshi

  • Takeo Kanade

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