• DocumentCode
    602446
  • Title

    Fast iterative five point relative pose estimation

  • Author

    Hedborg, J. ; Felsberg, Michael

  • Author_Institution
    Comput. Vision Lab., Linkoping Univ., Linkoping, Sweden
  • fYear
    2013
  • fDate
    15-17 Jan. 2013
  • Firstpage
    60
  • Lastpage
    67
  • Abstract
    Robust estimation of the relative pose between two cameras is a fundamental part of Structure and Motion methods. For calibrated cameras, the five point method together with a robust estimator such as RANSAC gives the best result in most cases. The current state-of-the-art method for solving the relative pose problem from five points is due to Nistér [9], because it is faster than other methods and in the RANSAC scheme one can improve precision by increasing the number of iterations. In this paper, we propose a new iterative method, which is based on Powell´s Dog Leg algorithm. The new method has the same precision and is approximately twice as fast as Nister´s algorithm. The proposed method is easily extended to more than five points while retaining a efficient error metrics. This makes it also very suitable as an refinement step. The proposed algorithm is systematically evaluated on three types of datasets with known ground truth.
  • Keywords
    cameras; image motion analysis; iterative methods; pose estimation; Dog Leg algorithm; RANSAC scheme; calibrated cameras; error metrics; fast iterative five point relative pose estimation; iterative method; motion method; precision improvement; robust relative pose estimation; structure method; Cameras; Equations; Estimation; Mathematical model; Noise level; Tracking; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robot Vision (WORV), 2013 IEEE Workshop on
  • Conference_Location
    Clearwater Beach, FL
  • Print_ISBN
    978-1-4673-5646-6
  • Electronic_ISBN
    978-1-4673-5647-3
  • Type

    conf

  • DOI
    10.1109/WORV.2013.6521915
  • Filename
    6521915