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首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >Calibration Method for Mapping Camera Based on a Precise Grouped Approach Method
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Calibration Method for Mapping Camera Based on a Precise Grouped Approach Method

机译:基于精确分组法的摄像机测绘标定方法

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摘要

This paper introduces a new calibration method for the mapping camera called Precise Grouped Approach Method (PGAM). The conventional calibration method for the mapping camera is the exact measuring angle method. The accuracy of this method can be reduced by theoretical uncertainties and the number and distribution of observation points. PGAM is able to overcome these disadvantages and improve the accuracy. Firstly, we reduce the theoretical uncertainties by means of a grouped approach method, which rectifies the high-precision rotation stage to zero position. Secondly, a weighted theory is applied to eliminate the effect of the number and distribution of observation points. Finally, the accuracy of PGAM is analyzed. The experiment result shows that the calibration accuracy is significantly improved when using the proposed PGAM algorithm, compared to the conventional one under the identical experimental condition.
机译:本文介绍了一种新的映射相机标定方法,称为精确分组方法(PGAM)。测绘相机的常规校准方法是精确测量角度法。该方法的准确性可能会因理论上的不确定性以及观察点的数量和分布而降低。 PGAM能够克服这些缺点并提高准确性。首先,我们通过分组逼近的方法减少了理论上的不确定性,该方法将高精度旋转台校正为零位置。其次,采用加权理论来消除观测点数量和分布的影响。最后,分析了PGAM的准确性。实验结果表明,与在相同实验条件下的常规算法相比,使用所提出的PGAM算法可以显着提高校准精度。

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