• DocumentCode
    2536764
  • Title

    Analysis of gesture and action in technical talks for video indexing

  • Author

    Ju, Shanon X. ; Black, Michael J. ; Minneman, Scott ; Kimber, Don

  • Author_Institution
    Dept. of Comput. Sci., Toronto Univ., Ont., Canada
  • fYear
    1997
  • fDate
    17-19 Jun 1997
  • Firstpage
    595
  • Lastpage
    601
  • Abstract
    We present an automatic system for analyzing and annotating video sequences of technical talks. Our method uses a robust motion estimation technique to detect key frames and segment the video sequence into subsequences containing a single overhead slide. The subsequences are stabilized to remove motion that occurs when the speaker adjusts their slides. Any changes remaining between frames in the stabilized sequences may be due to speaker gestures such as pointing or writing and we use active contours to automatically track these potential gestures. Given the constrained domain we define a simple “vocabulary” of actions which can easily be recognized based on the active contour shape and motion. The recognized actions provide a rich annotation of the sequence that can be used to access a condensed version of the talk from a web page
  • Keywords
    image segmentation; indexing; motion estimation; action; gesture; key frames; motion estimation; segment; technical talks; video indexing; video sequences; Computer science; Head; Image sequence analysis; Indexing; Motion detection; Robustness; Streaming media; Video sequences; Web pages; Writing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on
  • Conference_Location
    San Juan
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-7822-4
  • Type

    conf

  • DOI
    10.1109/CVPR.1997.609386
  • Filename
    609386