• DocumentCode
    469048
  • Title

    A gait recognition method based on positioning human body joints

  • Author

    Wang, Ai-hua ; Liu, Ji-wei

  • Author_Institution
    Univ. of Sci. & Technol. Beijing, Beijing
  • Volume
    3
  • fYear
    2007
  • fDate
    2-4 Nov. 2007
  • Firstpage
    1067
  • Lastpage
    1071
  • Abstract
    Gait recognition is to identify individuals by analysis of gait pattern. Here a simple and efficient gait recognition method based on positioning body joints is presented. At first key frame is extracted based on cyclic gait analysis. For each key frame image, background subtraction is performed to extract moving body silhouettes from the background. Then the coordinates of joints are computed according to the geometrical characteristics shown while walking. The limbs angles are computed based on the coordinates of joints and then made discrete Fourier transform. The amplitude-frequency and phase-frequency of angles are chosen as gait feature. At last the nearest neighbor classifier is used to classify subjects. Evaluation about the proposed gait recognition method is given according to experiment on the Soton gait database, and the experimental results demonstrate the encouraging performance.
  • Keywords
    discrete Fourier transforms; feature extraction; gait analysis; image recognition; image sequences; video signal processing; background subtraction; discrete Fourier transform; gait recognition; human body joint positioning; nearest neighbor classifier; silhouette feature extraction; video sequence; Humans; Information analysis; Joints; Leg; Legged locomotion; Nearest neighbor searches; Pattern analysis; Pattern recognition; Shoulder; Wavelet analysis; Gait recognition; key frame; limbs angles; position body joints; the nearest neighbor classifier;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-1065-1
  • Electronic_ISBN
    978-1-4244-1066-8
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2007.4421590
  • Filename
    4421590