• DocumentCode
    2472690
  • Title

    Gait recognition by dynamic cues

  • Author

    Bouchrika, Imed ; Nixon, Mark S.

  • Author_Institution
    Dept. of Electron. & Comput. Sci., Univ. of Southampton, Southampton, UK
  • fYear
    2008
  • fDate
    8-11 Dec. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Many studies have now shown that it is possible to recognize people by the way they walk. As yet there has been little formal study of people recognition using the kinematic-related gait features. We present a new method for gait recognition using dynamic features including the angular measurements of the lower limbs as well as the spatial displacement of the trunk. Gait signatures are derived using a feature selection algorithm which is based on a validation-criterion. We show that gait angular measurements derived from the joint motions mainly the ankle, knee and hip angles, possess most of the discriminatory potency for gait recognition with an achieved correct classification rate of 95.7%.
  • Keywords
    biometrics (access control); computer vision; feature extraction; gait analysis; image classification; image motion analysis; surveillance; automated recognition system; biometric; computer vision; dynamic cues; dynamic feature; feature selection algorithm; gait angular measurement; gait signature; human gait recognition; image classification; joint motion; kinematic-related gait feature; people recogntion; visual surveillance-and monitoring; Application software; Biometrics; Clothing; Data mining; Humans; Kinematics; Legged locomotion; Length measurement; Shape; Surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
  • Conference_Location
    Tampa, FL
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-2174-9
  • Electronic_ISBN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2008.4760994
  • Filename
    4760994