• DocumentCode
    3278700
  • Title

    Moving human tracking algorithm based on partial Hausdorff distance

  • Author

    Li, Li ; Xu Ji-ning

  • Author_Institution
    Coll. of Mech. & Electr. Eng., North China Univ. of Technol., Beijing, China
  • fYear
    2011
  • fDate
    15-17 April 2011
  • Firstpage
    5110
  • Lastpage
    5113
  • Abstract
    In order to realize accurate and fast tracking moving human, a moving human tracking algorithm based on partial Hausdorff distance is presented. This algorithm adopts Gaussian mixture distribution to model background of each pixel and background subtraction to detect moving regions. Shadow elimination and after treatment of moving regions provide moving human regions. Kalman filter is used to predict the position of tracking target in the next frame. Partial Hausdorff distance calculation is used to realize exact match, and the purpose of accurate and efficient tracking moving human can be reached. The experimental results show that the algorithm can continually track moving human accurately and fast despite occlusions and other moving object interference.
  • Keywords
    Gaussian processes; Kalman filters; object detection; object tracking; target tracking; Gaussian mixture distribution; Kalman filter; moving human tracking algorithm; moving region detection; partial Hausdorff distance; shadow elimination; target tracking; Computer vision; Conferences; Humans; Kalman filters; Niobium; Prediction algorithms; Target tracking; Hausdorff distance; moving human detection; target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Information and Control Engineering (ICEICE), 2011 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-8036-4
  • Type

    conf

  • DOI
    10.1109/ICEICE.2011.5777536
  • Filename
    5777536