• DocumentCode
    639503
  • Title

    Multi-agent Event Detection: Localization and Role Assignment

  • Author

    Kwak, Sangshin ; Bohyung Han ; Joon Hee Han

  • Author_Institution
    Dept. of Comput. Sci. & Eng., POSTECH, Pohang, South Korea
  • fYear
    2013
  • fDate
    23-28 June 2013
  • Firstpage
    2682
  • Lastpage
    2689
  • Abstract
    We present a joint estimation technique of event localization and role assignment when the target video event is described by a scenario. Specifically, to detect multi-agent events from video, our algorithm identifies agents involved in an event and assigns roles to the participating agents. Instead of iterating through all possible agent-role combinations, we formulate the joint optimization problem as two efficient sub problems-quadratic programming for role assignment followed by linear programming for event localization. Additionally, we reduce the computational complexity significantly by applying role-specific event detectors to each agent independently. We test the performance of our algorithm in natural videos, which contain multiple target events and nonparticipating agents.
  • Keywords
    computational complexity; image recognition; linear programming; multi-agent systems; quadratic programming; video signal processing; computational complexity; event localization; joint optimization problem; linear programming; multiagent event detection; multiple target events; natural videos; nonparticipating agents; quadratic programming; role assignment; role-specific event detectors; Estimation; Event detection; Hidden Markov models; Joints; Linear programming; Optimization; Vectors; activity detection; video event detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
  • Conference_Location
    Portland, OR
  • ISSN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2013.346
  • Filename
    6619190