• DocumentCode
    3135665
  • Title

    Exploratory factor analysis of gait recognition

  • Author

    Bouchrika, Imed ; Nixon, Mark S.

  • Author_Institution
    Dept. of Electron. & Comput. Sci., Univ. of Southampton, Southampton
  • fYear
    2008
  • fDate
    17-19 Sept. 2008
  • Firstpage
    1
  • Lastpage
    6
  • 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 the effects of covariates on the recognition process. We show how these factors can separately affect the walking pattern. Further we assess the contribution and discriminatory significance of the gait dynamics used for recognition. Based on a covariate-based probe dataset of 440 samples, a high recognition rate of 73.4% is achieved using the KNN classifier. This is to confirm that people identification using dynamic gait features is still perceivable with better recognition rate even under the different covariate factors.
  • Keywords
    biometrics (access control); gait analysis; image classification; surveillance; KNN classifier; biometrics; covariate-based probe dataset; dynamic gait feature; exploratory factor analysis; gait recognition; people identification; visual surveillance system; Biometrics; Cameras; Clothing; Face recognition; Fingerprint recognition; Footwear; Legged locomotion; Probes; Surveillance; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automatic Face & Gesture Recognition, 2008. FG '08. 8th IEEE International Conference on
  • Conference_Location
    Amsterdam
  • Print_ISBN
    978-1-4244-2153-4
  • Electronic_ISBN
    978-1-4244-2154-1
  • Type

    conf

  • DOI
    10.1109/AFGR.2008.4813395
  • Filename
    4813395