Robust Accurate Extrinsic Calibration of Static Non-overlapping Cameras

  • Andreas Robinson
  • Mikael Persson
  • Michael Felsberg
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10425)


An increasing number of robots and autonomous vehicles are equipped with multiple cameras to achieve surround-view sensing. The estimation of their relative poses, also known as extrinsic parameter calibration, is a challenging problem, particularly in the non-overlapping case. We present a simple and novel extrinsic calibration method based on standard components that performs favorably to existing approaches. We further propose a framework for predicting the performance of different calibration configurations and intuitive error metrics. This makes selecting a good camera configuration straightforward. We evaluate on rendered synthetic images and show good results as measured by angular and absolute pose differences, as well as the reprojection error distributions.



This work was funded in part by Vinnova, Sweden’s innovation agency, through grant iQmatic, Daimler AG, EC’s Horizon 2020 Programme, grant agreement CENTAURO and The Swedish Research Council through a framework grant for the project Energy Minimization for Computational Cameras (2014-6227).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Andreas Robinson
    • 1
  • Mikael Persson
    • 1
  • Michael Felsberg
    • 1
  1. 1.Linköping UniversityLinköpingSweden

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