• DocumentCode
    3201479
  • Title

    Tracking Multiple Objects using Probability Hypothesis Density Filter and Color Measurements

  • Author

    Pham, Nam Trung ; Huang, Weimin ; Ong, S.H.

  • Author_Institution
    Inst. for Infocomm Res., Singapore
  • fYear
    2007
  • fDate
    2-5 July 2007
  • Firstpage
    1511
  • Lastpage
    1514
  • Abstract
    Most methods for multiple object tracking in video represent the state of multi-object in a high dimensional joint state space. This leads to high computational complexity. This paper presents a method using the probability hypothesis density (PHD) filter to estimate the state of multiple objects in video. The method operates on the single object state space instead of the joint state space. A PHD recursion for visual observations with color measurements is proposed. Our method can track varying number of objects.
  • Keywords
    computational complexity; filtering theory; image colour analysis; probability; video signal processing; color measurements; computational complexity; high dimensional joint state space; multiple object tracking; probability hypothesis density filter; Colored noise; Density functional theory; Density measurement; Filtering; Filters; Histograms; Object detection; State-space methods; Surveillance; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2007 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    1-4244-1016-9
  • Electronic_ISBN
    1-4244-1017-7
  • Type

    conf

  • DOI
    10.1109/ICME.2007.4284949
  • Filename
    4284949