On-line Stereo Self-calibration through Minimization of Matching Costs

  • Robert Spangenberg
  • Tobias Langner
  • Raúl Rojas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7944)


This paper presents an approach to the problem of on-line stereo self-calibration. After a short introduction of the general method, we propose a new one, based on the minimization of matching costs. We furthermore show that the number of matched pixels can be used as a quality measure. A Metropolis algorithm based Monte-Carlo scheme is employed to reliably minimize the costs. We present experimental results in the context of automotive stereo with different matching algorithms. These show the effectiveness for the calibration of roll and pitch angle offsets.


self-calibration stereo vision matching costs 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Robert Spangenberg
    • 1
  • Tobias Langner
    • 1
  • Raúl Rojas
    • 1
  1. 1.Institut für InformatikFreie Universität BerlinBerlinGermany

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