Camera calibration is crucial for geometric vision-based three-dimensional (3D) deformation measurement tasks. Among existing calibration techniques, the one based on planar targets has attracted much attention in the community due to its flexibility and reliability. Our study proposes a calibration technique to obtain high-accuracy internal and external parameters based on low-cost ordinary planar patterns. The proposed method determines the optimal internal parameters for each camera by refining 3D coordinates of planar control points, where an analytic model of optics distortion is presented to enable lens distortion to be corrected directly in subsequent external calibration and underlying 3D reconstruction. External parameters are estimated by minimizing a bundle adjustment framework, which is carefully designed based on the proposed distortion correction model and depth parameterization. In contrast to the existing techniques, the proposed method is capable of obtaining a high-accuracy calibration with ordinary targets rather than the well-designed and fabricated ones. We experimented the proposed method with a calibration performance analysis and a displacement measurement; both results demonstrated the accuracy and robustness.

中文翻译：

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基于普通平面图案和解析变形模型的三维视觉位移测量中的高精度相机校准

相机校准对于基于几何视觉的三维（3D）变形测量任务至关重要。在现有的校准技术中，一种基于平面目标的校准技术因其灵活性和可靠性而备受关注。我们的研究提出了一种校准技术，可基于低成本的普通平面图案获得高精度的内部和外部参数。所提出的方法通过细化平面控制点的3D坐标来确定每个摄像机的最佳内部参数，其中提出了光学畸变的解析模型，可以在后续的外部校准和基础3D重建中直接校正镜头畸变。外部参数是通过最小化捆绑调整框架来估算的，在建议的失真校正模型和深度参数化的基础上进行了精心设计。与现有技术相反，所提出的方法能够通过普通目标而不是经过精心设计和制造的目标来获得高精度校准。我们通过校准性能分析和位移测量对提出的方法进行了实验；这两个结果都证明了准确性和鲁棒性。