• DocumentCode
    2304296
  • Title

    Particle filter based on multi-window

  • Author

    Guo Dugang ; Ding Xilong ; Zhen XinQing ; Liu Yan ; Meng Qiang

  • Author_Institution
    Sino-India Software Inst., Weifang Univ. of Sci. & Technol., Weifang, China
  • fYear
    2012
  • fDate
    29-31 Dec. 2012
  • Firstpage
    1776
  • Lastpage
    1779
  • Abstract
    A novel particle filter based on multi-window is proposed for target tracking, which represents the tracking target with several windows that each one corresponds with a particle filter. Because tracking performance is usually influenced by factors such as camera angle, illumination. Meanwhile the target may be occluded by obstacles in the clutter background or be occluded by other target. A multi-window particle filter tracking method is proposed. And the multi-window may overlap or contain the scene around the target. In the tracking process, the different particles have different tracking cues of the targets. In the novel algorithm, through the spatial relation of the non-overlap windows and overlap windows, the spatial configuration of the tracking target is included and considered. All particle filter trackers are used to estimate the target status parameters. Using this algorithm, we can overcome the tracking failure because of the object spatial features considered. And experiment results clearly demonstrate the effectiveness of the novel method on illumination influence or self-occlusion problem in a complex background.
  • Keywords
    computer vision; particle filtering (numerical methods); target tracking; camera angle; computer vision; illumination; multiwindow particle filter tracking method; nonoverlap windows; occlusion; overlap windows; spatial relation; target tracking; tracking performance; multi-windows; particle filter; target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4673-2963-7
  • Type

    conf

  • DOI
    10.1109/ICCSNT.2012.6526264
  • Filename
    6526264