• DocumentCode
    2178970
  • Title

    A Review of Vision-Based Gait Recognition Methods for Human Identification

  • Author

    Wang, Jin ; She, Mary ; Nahavandi, Saeid ; Kouzani, Abbas

  • Author_Institution
    Inst. for Technol. Res. & Innovation, Deakin Univ., Waurn Ponds, VIC, Australia
  • fYear
    2010
  • fDate
    1-3 Dec. 2010
  • Firstpage
    320
  • Lastpage
    327
  • Abstract
    Human identification by gait has created a great deal of interest in computer vision community due to its advantage of inconspicuous recognition at a relatively far distance. This paper provides a comprehensive survey of recent developments on gait recognition approaches. The survey emphasizes on three major issues involved in a general gait recognition system, namely gait image representation, feature dimensionality reduction and gait classification. Also, a review of the available public gait datasets is presented. The concluding discussions outline a number of research challenges and provide promising future directions for the field.
  • Keywords
    computer vision; gait analysis; image classification; image motion analysis; image representation; computer vision; feature dimensionality reduction; gait classification; gait image representation; gait recognition methods; human identification; inconspicuous recognition; public gait datasets; Biological system modeling; Computational modeling; Feature extraction; Hidden Markov models; Humans; Legged locomotion; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Image Computing: Techniques and Applications (DICTA), 2010 International Conference on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    978-1-4244-8816-2
  • Electronic_ISBN
    978-0-7695-4271-3
  • Type

    conf

  • DOI
    10.1109/DICTA.2010.62
  • Filename
    5692583