• DocumentCode
    2610991
  • Title

    Gesture Detection in Low-Quality Video

  • Author

    Roh, Myung-Cheol ; Lee, Seong-Whan

  • Author_Institution
    Center for Artificial Vision Res., Korea Univ., Seoul
  • Volume
    4
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    791
  • Lastpage
    794
  • Abstract
    The spotting and recognition of the human gestures is a key task in automating the analysis of the video material and human-robot interaction. Specially applying this technology to low-resolution video has many potential applications. The human area is small with respect to input video frames in broadcast sports video, surveillance video, etc. However, this condition makes the spotting certain gesture in a video sequence a challenging task, especially if there is large camera motion. To overcome the problems, we propose a posture matching method based on curvature scale space templates of the human silhouette. We also propose a new recognition method which is robust to noisy sequences of data
  • Keywords
    feature extraction; gesture recognition; image matching; image motion analysis; image representation; image sequences; video signal processing; camera motion; curvature scale space templates; gesture detection; human gesture recognition; human silhouette; human-robot interaction; low-quality video; low-resolution video; posture matching; video analysis; video frames; video sequence; Broadcasting; Cameras; Cascading style sheets; Feature extraction; Humans; Robustness; Space technology; Spatial databases; Surveillance; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.607
  • Filename
    1699959