• DocumentCode
    357115
  • Title

    Real-time scene change detection on compressed multimedia bitstream based on statistical sequential analysis

  • Author

    Lelescu, Dan ; Schonfeld, Dan

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, IL, USA
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1141
  • Abstract
    In this paper, a novel one-pass, real-time approach to video scene change detection based on statistical sequential analysis and operating on a compressed multimedia bitstream is proposed. Scene change detection is crucial in that it enables subsequent processing operations on video shots, such as video indexing, semantic representation, or tracking of selected video information. Since video sequences contain both abrupt and gradual scene changes, video segmentation algorithms must be able to detect a large variety of changes. Our approach models video sequences as stochastic processes, with scene changes being reflected by changes in the characteristics (parameters) of the process. We use statistical sequential analysis to provide a unified framework for robust and effective detection of both abrupt and gradual scene changes
  • Keywords
    data compression; image segmentation; image sequences; multimedia systems; real-time systems; statistical analysis; stochastic processes; video coding; compressed multimedia bitstream; one-pass real-time approach; real-time scene change detection; semantic representation; statistical sequential analysis; stochastic processes; video indexing; video scene change; video segmentation; video sequences; video shots; Change detection algorithms; Electronic mail; Gunshot detection systems; Layout; Sequential analysis; Statistical analysis; Stochastic processes; Transform coding; Video compression; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2000. ICME 2000. 2000 IEEE International Conference on
  • Conference_Location
    New York, NY
  • Print_ISBN
    0-7803-6536-4
  • Type

    conf

  • DOI
    10.1109/ICME.2000.871562
  • Filename
    871562