• DocumentCode
    3221152
  • Title

    A three-mode expressive feature model of action effort

  • Author

    Davis, James W. ; Gao, Hui ; Kannappan, Vignesh S.

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Ohio State Univ., Columbus, OH, USA
  • fYear
    2002
  • fDate
    5-6 Dec. 2002
  • Firstpage
    139
  • Lastpage
    144
  • Abstract
    We present an expressive feature model for recognizing the performance effort of human actions. A set of low and high effort examples for an action are initially factored into its three-mode principal components, followed by a learning phase to compute the expressive features required to bring the model estimation of effort into agreement with perceptual judgements. The approach is demonstrated using real and illusory movements.
  • Keywords
    computer vision; gait analysis; image motion analysis; learning (artificial intelligence); parameter estimation; principal component analysis; video signal processing; athletic training; computer vision; ergonomic monitoring system; expressive feature model; human action effort estimation; learning phase; motion-capture animations; perceptual dynamics; surveillance systems; three-mode principal components; video annotation; Animation; Computational intelligence; Hidden Markov models; Humans; Information science; Injuries; Legged locomotion; Packaging; Patient monitoring; Phase estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Motion and Video Computing, 2002. Proceedings. Workshop on
  • Print_ISBN
    0-7695-1860-5
  • Type

    conf

  • DOI
    10.1109/MOTION.2002.1182226
  • Filename
    1182226