• DocumentCode
    2287653
  • Title

    Quasi-periodic event analysis for social game retrieval

  • Author

    Wang, Ping ; Abowd, Gregory D. ; Rehg, James M.

  • Author_Institution
    Health Systems Institute and GVU Center, School of Interactive Computing, Georgia Institute of Technology, USA
  • fYear
    2009
  • fDate
    Sept. 29 2009-Oct. 2 2009
  • Firstpage
    112
  • Lastpage
    119
  • Abstract
    A new problem of retrieving social games from unstructured videos is proposed. Social games are characterized by repetitions (with variations) of alternating turns between two players. We define games as quasi-periodic motion patterns in video based on their repetitiveness property. We have developed an algorithm to extract such patterns from video. The patterns extracted by our method, from video clips of social games taken from YouTube, are shown to correspond to meaningful stages of the games. We demonstrate promising results in retrieving social games from unstructured, lab-recorded footage of children´s play, and identifying social interactions in a dataset of approximately 3.75 hours of home movies.
  • Keywords
    Cameras; Computer vision; Data mining; Games; Information retrieval; Motion analysis; Motion estimation; Motion pictures; Pediatrics; Videos;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 2009 IEEE 12th International Conference on
  • Conference_Location
    Kyoto
  • ISSN
    1550-5499
  • Print_ISBN
    978-1-4244-4420-5
  • Electronic_ISBN
    1550-5499
  • Type

    conf

  • DOI
    10.1109/ICCV.2009.5459151
  • Filename
    5459151