• DocumentCode
    384445
  • Title

    Temporal PDMs for gait classification

  • Author

    Tassone, Ezra ; West, Geoff ; Venkatesh, Svetha

  • Author_Institution
    Sch. of Comput. Sci., Curtin Univ. of Technol., Perth, WA, Australia
  • Volume
    2
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    1065
  • Abstract
    Gait classification is a developing research area, particularly with regards to biometrics. It aims to use the distinctive spatial and temporal characteristics of human motion to classify differing activities. As a biometric, this extends to recognising different people by the heterogeneous aspects of their gait. This research aims to use a modified deformable model, the temporal PDM, to distinguish the movements of a walking and running person. The movement of 2D points on the moving form is used to provide input into the model and classify the type of gait present.
  • Keywords
    biometrics (access control); gait analysis; image motion analysis; 2D point movement; biometrics; gait classification; human motion; modified deformable model; person recognition; running person; spatial characteristics; temporal PDM; temporal characteristics; walking person; Australia; Biometrics; Covariance matrix; Deformable models; Eigenvalues and eigenfunctions; Humans; Image recognition; Legged locomotion; Optical films; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2002. Proceedings. 16th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-1695-X
  • Type

    conf

  • DOI
    10.1109/ICPR.2002.1048489
  • Filename
    1048489