• DocumentCode
    159735
  • Title

    Background subtraction-based multiple object tracking using particle filter

  • Author

    Intaek Kim ; Awan, Tayyab Wahab ; Youngsung Soh

  • Author_Institution
    Dept. of Inf. & Commun. Eng., Myongji Univ., Yongin, South Korea
  • fYear
    2014
  • fDate
    12-15 May 2014
  • Firstpage
    71
  • Lastpage
    74
  • Abstract
    In surveillance system, many vision based methods are utilized for multiple objects. Some of the methods used for tracking include background modeling, Kalman filter, particle filter etc. The proposed method combines both the background modeling and particle filter to track multiple objects. This method consists of two steps: background subtraction and application of particle filter. Background subtraction restricts the area of search so that the particle filter performs efficiently. Different colored particles are displayed on the object for tracking. After applying the proposed method on a video having multiple objects, successful results were obtained.
  • Keywords
    Kalman filters; computer vision; object tracking; particle filtering (numerical methods); video surveillance; Kalman filter; background modeling; background subtraction-based multiple object tracking; particle filter; surveillance system; video; vision based methods; Business; Europe; Kalman filters; Tracking; Background Subtraction; Particle filter; Reference frame; Tracking using particles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Signals and Image Processing (IWSSIP), 2014 International Conference on
  • Conference_Location
    Dubrovnik
  • ISSN
    2157-8672
  • Type

    conf

  • Filename
    6837633