• DocumentCode
    2713932
  • Title

    A new mirror-based extrinsic camera calibration using an orthogonality constraint

  • Author

    Takahashi, Kosuke ; Nobuhara, Shohei ; Matsuyama, Takashi

  • Author_Institution
    Grad. Sch. of Inf., Kyoto Univ., Kyoto, Japan
  • fYear
    2012
  • fDate
    16-21 June 2012
  • Firstpage
    1051
  • Lastpage
    1058
  • Abstract
    This paper is aimed at calibrating the relative posture and position, i.e. extrinsic parameters, of a stationary camera against a 3D reference object which is not directly visible from the camera. We capture the reference object via a mirror under three different unknown poses, and then calibrate the extrinsic parameters from 2D appearances of reflections of the reference object in the mirrors. The key contribution of this paper is to present a new algorithm which returns a unique solution of three P3P problems from three mirrored images. While each P3P problem has up to four solutions and therefore a set of three P3P problems has up to 64 solutions, our method can select a solution based on an orthogonality constraint which should be satisfied by all families of reflections of a single reference object. In addition we propose a new scheme to compute the extrinsic parameters by solving a large system of linear equations. These two points enable us to provide a unique and robust solution. We demonstrate the advantages of the proposed method against a state-of-the-art by qualitative and quantitative evaluations using synthesized and real data.
  • Keywords
    calibration; cameras; image processing; mirrors; 3D reference object; mirror based extrinsic camera calibration; orthogonality constraint; relative position; relative posture; stationary camera; Calibration; Cameras; Eigenvalues and eigenfunctions; Equations; Mathematical model; Mirrors; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
  • Conference_Location
    Providence, RI
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4673-1226-4
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2012.6247783
  • Filename
    6247783