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PEI Ming-tao, YU Lian-qing, LIU Peng, JIA Yun-de. Camera Self-Calibration in Computer Vision with Precise Estimation of Initial Parameters[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2004, 13(2): 152-156.
Citation: PEI Ming-tao, YU Lian-qing, LIU Peng, JIA Yun-de. Camera Self-Calibration in Computer Vision with Precise Estimation of Initial Parameters[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2004, 13(2): 152-156.

Camera Self-Calibration in Computer Vision with Precise Estimation of Initial Parameters

Funds:SponsoredbytheNationalNaturalScienceFoundation(K60075005)
  • Received Date:2003-04-22
  • A key problem that plagues camera self-calibration, namely that the classical self-calibration algorithms are very sensitive to the initial values of the camera intrinsic parameters, is analyzed and a practical solution is provided. The effect of the camera intrinsic parameters, mainly the principal point and the skew factor is first discussed. Then a practical method via a controlled motion of the camera is introduced so as to obtain an accurate estimation of these parameters. Feasibility of this approach is illustrated by carrying out comprehensive experiments using synthetic data as well as real image sequences. Unreasonable initial values can often make self-calibration impossible, yet a precise initialization guarantees a better and successful reconstruction. Trying to obtain a more reasonable initialization is worthwhile the effort in camera self-calibration.
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