• DocumentCode
    2066363
  • Title

    Adaptive particle filter based pose estimation using a monocular camera model

  • Author

    Goli, Mohammad ; Ghanbari, Ahmad ; Janabi-Sharifi, Farrokh ; Khosroshahi, Ghader Karimian

  • Author_Institution
    Sch. of Eng., Emerging Technol. Univ. of Tabriz, Tabriz, Iran
  • fYear
    2010
  • fDate
    25-27 Oct. 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Camera full pose estimation using only a monocular camera model is an important topic in the field of visual servoing. In this paper a simple adaptive method for updating the weights of particle filter is proposed. Using this method, the efficiency of particle filter in estimating the full pose of camera is improved. Results of the proposed method are compared with those of generic particle filter (PF) and EKF under the same condition through an intensive computer simulation.
  • Keywords
    cameras; particle filtering (numerical methods); pose estimation; visual servoing; adaptive particle filter; intensive computer simulation; monocular camera model; pose estimation; visual servoing; Atmospheric measurements; Cameras; Computational modeling; Estimation; Hidden Markov models; Particle filters; Particle measurements; Bayesian filter; extended Kalman filter; particle filter; pose estimation; visual servoing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Optomechatronic Technologies (ISOT), 2010 International Symposium on
  • Conference_Location
    Toronto, ON
  • Print_ISBN
    978-1-4244-7684-8
  • Type

    conf

  • DOI
    10.1109/ISOT.2010.5687313
  • Filename
    5687313