• DocumentCode
    1719304
  • Title

    Meanshift algorithm based on kernel bandwidth adaptive adjust

  • Author

    Yunji Zhao ; Hailong Pei ; Baoluo Liu

  • Author_Institution
    Sch. of Electr. Eng. & Autom., Henan Polytech. Univ., Jiaozuo, China
  • fYear
    2013
  • Firstpage
    4486
  • Lastpage
    4490
  • Abstract
    Object tracking algorithm based on Meanshift algorithm with fixed kernel bandwidth does not realize object tracking correctly with the scale of object changed. According to this, a scheme of kernel bandwidth adaptive adjustment and predictions of object cancroids based on Kalman filter is proposed in this paper. In this algorithm, Object location predicted based on Kalman filter is used to initialize the Meanshift algorithm. The variation tendency of the kernel bandwidth is also determined based on Kalman filter. Experiment results demonstrate that this algorithm can realize the kernel bandwidth adaptive adjustment and object location prediction. The robustness of the tracking algorithm is also enhanced.
  • Keywords
    Kalman filters; object tracking; Kalman filter; fixed-kernel bandwidth adaptive adjustment; kernel bandwidth variation tendency; meanshift algorithm initialization; object cancroid predictions; object location prediction; object tracking algorithm robustness enhancement; Bandwidth; Conferences; Electronic mail; Kalman filters; Kernel; Prediction algorithms; Robustness; Kalman Filter; Kernel Bandwidth; Meanshift Algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2013 32nd Chinese
  • Conference_Location
    Xi´an
  • Type

    conf

  • Filename
    6640210