• DocumentCode
    2621683
  • Title

    The extraction and effective identification of human motion characteristics for video images

  • Author

    Li, Dianmei ; Zhao, Hui ; Chang, Shuhui

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Shandong Univ., Jinan, China
  • fYear
    2011
  • fDate
    27-29 June 2011
  • Firstpage
    3697
  • Lastpage
    3700
  • Abstract
    The identification of the body motion for video images with computer visual technology is analyzing and dealing with the video or sequence of images. It can detect the human motion target, extract the motion characteristics in order to understanding the movement and identifying the person. This paper has introduced a new algorithm for the extraction and effective identification of human motion characteristics for video images. The method fuses seven Hu moment invariants of the human body contour and the feature of limbs angles for motion information. Different features have different weights. Finally a nearest neighbor fuzzy classifier is used to classify subjects. This method can effectively solve the problem of a number of data and complex calculations. Experimental results show that the proposed algorithm has effective recognition performance.
  • Keywords
    artificial limbs; computer vision; feature extraction; gait analysis; image classification; image sequences; motion estimation; object detection; video signal processing; body motion identification; computer visual technology; feature extraction; human body contour; image sequence; limbs angles; nearest neighbor fuzzy classifier; target detection; video images; Computers; Educational institutions; Humans; Information science; Information theory; Pattern recognition; Target recognition; Hu moment invariants; feature fusion; human motion characteristic; joint angles of limbs; the nearest neighbor fuzzy classifier;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Service System (CSSS), 2011 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-9762-1
  • Type

    conf

  • DOI
    10.1109/CSSS.2011.5974745
  • Filename
    5974745