• DocumentCode
    1704371
  • Title

    Front-view Gait Recognition

  • Author

    Goffredo, Michela ; Carter, John N. ; Nixon, Mark S.

  • Author_Institution
    Sch. of Electron. & Comput. Sci., Univ. of Southampton, Southampton
  • fYear
    2008
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    We present a new method for front-view gait biometrics which uses a single non-calibrated camera and extracts unique signatures from descriptors of a silhouette´s deformation. The proposed approach is particularly suitable for identification by gait in the real world, where the advantages of completely unobtrusiveness, remoteness and covertness of the biometric system preclude the availability of camera information and where the CCTV images usually present subjects from an upper front-view. Tests on three different gait databases with subjects walking towards the camera have been performed. The obtained results, with mean CCR of 96.3%, show that gait recognition of individuals observed the front can be achieved without any knowledge of camera parameters. Moreover, the method has been applied to three different walking directions and the results have been compared with the algorithms found in literature. The performance of the proposed system is particularly encouraging for its appliance in surveillance scenarios.
  • Keywords
    biometrics (access control); gesture recognition; image sensors; surveillance; front-view gait biometrics; front-view gait recognition; gait databases; noncalibrated camera; surveillance scenarios; Availability; Biometrics; Cameras; Data mining; Home appliances; Image databases; Legged locomotion; Performance evaluation; Surveillance; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biometrics: Theory, Applications and Systems, 2008. BTAS 2008. 2nd IEEE International Conference on
  • Conference_Location
    Arlington, VA
  • Print_ISBN
    978-1-4244-2729-1
  • Electronic_ISBN
    978-1-4244-2730-7
  • Type

    conf

  • DOI
    10.1109/BTAS.2008.4699356
  • Filename
    4699356