• DocumentCode
    2243059
  • Title

    Video Frame Identification for Learning Media Content Understanding

  • Author

    Li, Ying ; Dorai, Chitra

  • Author_Institution
    IBM Thomas J. Watson Res. Center, Hawthorne, NY
  • fYear
    2005
  • fDate
    6-6 July 2005
  • Firstpage
    1488
  • Lastpage
    1491
  • Abstract
    This paper presents our latest work on identifying frame content types for understanding learning media content. In particular, we categorize frames into six classes namely, slide, Web-page, instructor, audience, picture-in-picture and miscellaneous, which make up salient narrative modes in learning videos. Various image and video analysis approaches are explored to achieve this task. Preliminary experiments carried out on three recorded seminars have yielded encouraging results. The identification of fine-grained visual content types can assist us in content understanding, access, browsing and searching of generic learning videos
  • Keywords
    content-based retrieval; learning (artificial intelligence); video retrieval; video signal processing; fine-grained visual content; generic learning videos; image analysis; media content understanding; video frame identification; Character recognition; Educational institutions; Educational programs; Electronic learning; Face recognition; Histograms; Image analysis; Industrial training; Internet; Seminars;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on
  • Conference_Location
    Amsterdam
  • Print_ISBN
    0-7803-9331-7
  • Type

    conf

  • DOI
    10.1109/ICME.2005.1521714
  • Filename
    1521714