S3-R1: the IBM smart surveillance system-release 1

  • Authors:
  • Arun Hampapur;Lisa Brown;Jonathan Connell;Norman Haas;Max Lu;Hans Merkl;Sharat Pankanti;Andrew Senior;Chiao-Fe Shu;Yingli Tian

  • Affiliations:
  • IBM T.J. Watson Research Center, Hawthorne, NY;IBM T.J. Watson Research Center, Hawthorne, NY;IBM T.J. Watson Research Center, Hawthorne, NY;IBM T.J. Watson Research Center, Hawthorne, NY;IBM T.J. Watson Research Center, Hawthorne, NY;IBM T.J. Watson Research Center, Hawthorne, NY;IBM T.J. Watson Research Center, Hawthorne, NY;IBM T.J. Watson Research Center, Hawthorne, NY;IBM T.J. Watson Research Center, Hawthorne, NY;IBM T.J. Watson Research Center, Hawthorne, NY

  • Venue:
  • Proceedings of the 2004 ACM SIGMM workshop on Effective telepresence
  • Year:
  • 2004

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Abstract

One of the key components of tele-presence systems is automatic awareness of the remote environment. This very same capability of automatic situation awareness is currently being developed and deployed in the context of the next generation smart surveillance systems. Smart surveillance systems use a number of automatic video analysis techniques like object detection, tracking and classification in conjunction with database and web application servers to provide users with the capability of distributed smart surveillance. The IBM smart surveillance system is one of the few advanced surveillance systems which provides not only the capability to automatically monitor a scene but also the capability to manage the surveillance data, perform event based retrieval, receive real time event alerts thru standard web infrastructure and extract long term statistical patterns of activity.