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Comparing Self-calibration Methods for Static Cameras

  • J. Isern González
  • J. Cabrera Gámez
  • J. D. Hernández Sosa
  • A. C. Domínguez Brito
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4739)

Abstract

Many methods have been developed in the last few years to self-calibrate cameras, but few works have addressed the comparison of such methods to provide the user with hints on the suitability of certain algorithms under particular circumstances. This work presents a comparative analysis of four self-calibration methods for cameras which only rotate. This paper concentrates on the stability, the accuracy in the estimation of each parameter and the computational cost. This study has been carried out with real and simulated images. The experiments have shown that the optic center is the most unstable parameter for all methods and that the greatest discrepancies among the estimated values appear with the scale factors. Also, there are no correspondence among image disparity and parameters error. Finally, the results returned by any of these methods are comparable in terms of accuracy with those provided by a well-known manual calibration method.

Keywords

Global Error Camera Calibration Intrinsic Parameter Optic Center Camera Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • J. Isern González
    • 1
  • J. Cabrera Gámez
    • 1
  • J. D. Hernández Sosa
    • 1
  • A. C. Domínguez Brito
    • 1
  1. 1.Instituto Universitario de Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (IUSIANI), Universidad de Las Palmas de Gran Canaria, Spain, LAS PALMAS 35017 

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