• DocumentCode
    3342512
  • Title

    Omni-directional Vision Localization Based on Particle Filter

  • Author

    Cao, Zuoliang ; Liu, Shiyu ; Röning, Juha

  • Author_Institution
    Tianjin Univ. of Technol., Tianjin
  • fYear
    2007
  • fDate
    22-24 Aug. 2007
  • Firstpage
    478
  • Lastpage
    483
  • Abstract
    Omni-directional vision navigation appears definite significant since its advantage of panoramic sight with a single compact visual scene. This unique guidance technique involves target recognition, vision tracking, object positioning, path programming. An algorithm for omni-vision based global localization which utilizes two overhead features as beacon pattern is proposed in this paper. An approach for geometric restoration of omni-vision images has to be considered since an inherent distortion exists. The localization of the robot can be achieved by geometric computation. Dynamic localization employs a beacon tracker to follow the landmarks in real time during the arbitrary movement of the vehicle. Particle filter (PF) has been shown to be successful for several nonlinear estimation problems. A beacon tracker based on Particle filter which offers a probabilistic framework for dynamic state estimation in visual tracking has been developed. We have implemented the tracking and localization system and demonstrated the relevant of the algorithm.
  • Keywords
    computer vision; image recognition; image restoration; nonlinear estimation; particle filtering (numerical methods); probability; target tracking; beacon tracker; dynamic localization; dynamic state estimation; geometric restoration; global localization; guidance technique; nonlinear estimation problems; object positioning; omnidirectional vision localization; particle filter; path programming; target recognition; vision tracking; Image restoration; Layout; Navigation; Nonlinear distortion; Particle filters; Particle tracking; Robot programming; Target recognition; Target tracking; Vehicle dynamics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Graphics, 2007. ICIG 2007. Fourth International Conference on
  • Conference_Location
    Sichuan
  • Print_ISBN
    0-7695-2929-1
  • Type

    conf

  • DOI
    10.1109/ICIG.2007.145
  • Filename
    4297133