Camera self-calibration under the constraint of distant plane

  • Authors:

  • Guanghui Wang;Q. M. Jonathan Wu;Wei Zhang

  • Affiliations:

  • Department of Electrical and Computer Engineering, The University of Windsor, Windsor, Ontario, Canada and Department of Control Engineering, Aviation University, Changchun, Jilin, P.R. China;Department of Electrical and Computer Engineering, The University of Windsor, Windsor, Ontario, Canada;Department of Electrical and Computer Engineering, The University of Windsor, Windsor, Ontario, Canada

  • Venue:
  • RobVis'08 Proceedings of the 2nd international conference on Robot vision
  • Year:
  • 2008

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Abstract

Kruppa equation based camera self-calibration is one of the classical problems in computer vision. Most state-of-the-art approaches directly solve the quadratic constraints derived from Kruppa equations, which are computationally intensive and difficult to obtain initial values. In this paper, we propose a new initialization algorithm by estimating the unknown scalar in the equation, thus the camera parameters can be computed linearly in a closed form and then refined iteratively via global optimization techniques. We prove that the scalar can be uniquely recovered from the infinite homography and propose a practical method to estimate the homography from a physical or virtual plane located at a far distance to the camera. Extensive experiments on synthetic and real images validate the effectiveness of the proposed method.