基于一阶径向畸变算法的双目摄像机多位姿标定方法

双目立体视觉中在对物体进行三维测量或精准定位时，需要对摄像机进行标定以获得其内外参数。研究径向畸变摄像机模型，构造了基于一阶径向畸变（RAC）算法的双目摄像机内外参数线性求解公式。考虑侧倾角、旋转角、俯仰角以及透镜的主要畸变因素，修正了传统RAC标定法中只考虑径向畸变、部分参数需要先验值的缺陷。利用标定所得内、外参数进行了多位姿双目摄像机三维重构实验。实验结果表明，该标定方法重投影误差分布在-0.3，0.3]，动态识别结果与实际运行轨迹重合率为96%，对降低双目立体视觉三维测量误差率有积极性影响。

Binocular camera multi-pose calibration method based on radial alignment constraint algorithm

In binocular stereo vision, the camera needs to be calibrated to obtain its internal and external parameters in 3D measurement or precise positioning of the object.Through the study of the camera model with first-order radial distortion, linear formulas of solving internal and external parameters were constructed based on Radial Alignment Constraint (RAC) calibration method. Inclination angle, rotation angle, pitch angle and main distortion elements of lens were taken into consideration in this algorithm, which modified the defects in the traditional RAC calibration method that it only considers radial distortion and some parameters need priori values. The 3D reconstruction experiment of multi-pose binocular camera was carried out by using the obtained internal and external parameters. The experimental results show that,the reprojection error of this calibration method is distributed in-0.3,0.3], and the similarity between the measurement trajectory and the actual trajectory is 96%, which has a positive effect on reducing the error rate of binocular stereo vision 3D measurement.