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Robust Camera Calibration using Discrete Optimization

Authors: Stephan Rupp, Matthias Elter, Michael Breitung, Walter Zink, Christian Küblbeck

Abstract:

Camera calibration is an indispensable step for augmented reality or image guided applications where quantitative information should be derived from the images. Usually, a camera calibration is obtained by taking images of a special calibration object and extracting the image coordinates of projected calibration marks enabling the calculation of the projection from the 3d world coordinates to the 2d image coordinates. Thus such a procedure exhibits typical steps, including feature point localization in the acquired images, camera model fitting, correction of distortion introduced by the optics and finally an optimization of the model-s parameters. In this paper we propose to extend this list by further step concerning the identification of the optimal subset of images yielding the smallest overall calibration error. For this, we present a Monte Carlo based algorithm along with a deterministic extension that automatically determines the images yielding an optimal calibration. Finally, we present results proving that the calibration can be significantly improved by automated image selection.

Keywords: Camera Calibration, Discrete Optimization, Monte Carlo Method.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1328452

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References:


[1] Edward Mikhail Chris McGlone. Manual of Photogrammetry. ASPRS, 5 edition, 2004.
[2] M. A. Fischler and R.C. Bolles. Random sampling consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Comm. of the ACM, 24:381 - 395, 1981.
[3] Janne Heikkil¨a and Olli Silv'en. A four-step camera calibration procedure with implicit image correction. IEEE Conference on Computer Vision and Pattern Recognition, pages 1106-1112, June 1997.
[4] Janne Heikkil¨a and Olli Silv'en. Geometric camera calibration using circular control points. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(10):1066 - 1077, October 2000.
[5] G.G. Mateos. A camera calibration technique using targets of circular features. 5th Ibero-America Symposium On Pattern Recognition (SIARP), 2000.
[6] Jean-Nicolas Ouellet and Patrick H'ebert. Developing assistant tools for geometric camera calibration: Assessing the quality of input images. In ICPR (4), pages 80-83, 2004.
[7] Rangaraj M. Rangayyan, N. M. El-Faramawy, J. E. Leo Desautels, and Onsy Abdel Alim. Measures of acutance and shape for classification of breast tumors. IEEE Trans. Med. Imaging, 16(6):799-810, 1997.
[8] Peter Sturm and Steve Maybank. On plane-based camera calibration: A general algorithm, singularities, applications. In IEEE Conference on Computer Vision and Pattern Recognition, pages 432-437, June 1999.
[9] Roger Y. Tsai. A versatile camera calibration technique for highaccuaricy 3d machine vision metrology using off-the-shelf tv cameras and lenses. IEEE Transactions on Robotics and Automation, 4:323 - 344, August 1987.
[10] Zhengyou Zhang. A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11):1330-1334, 2000.