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      High-accuracy and robust localization of large control markers for geometric camera calibration.

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          Abstract

          Accurate measurement of the position of features in an image is subject to a fundamental compromise: The features must be both small, to limit the effect of nonlinear distortions, and large, to limit the effect of noise and discretization. This constrains both the accuracy and the robustness of image measurements, which play an important role in geometric camera calibration as well as in all subsequent measurements based on that calibration. In this paper, we present a new geometric camera calibration technique that exploits the complete camera model during the localization of control markers, thereby abolishing the marker size compromise. Large markers allow a dense pattern to be used instead of a simple disc, resulting in a significant increase in accuracy and robustness. When highly planar markers are used, geometric camera calibration based on synthetic images leads to true errors of 0.002 pixels, even in the presence of artifacts such as noise, illumination gradients, compression, blurring, and limited dynamic range. The camera parameters are also accurately recovered, even for complex camera models.

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          Author and article information

          Journal
          IEEE Trans Pattern Anal Mach Intell
          IEEE transactions on pattern analysis and machine intelligence
          Institute of Electrical and Electronics Engineers (IEEE)
          0162-8828
          0098-5589
          Feb 2009
          : 31
          : 2
          Affiliations
          [1 ] Image Processing Laboratory, NAIST, Ikoma, Japan. d.douxchamps@ieee.org
          Article
          10.1109/TPAMI.2008.214
          19110502
          73544afd-724e-4159-9523-c021cf0708d2
          History

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