Stereo vision (SV) is widely used for noncontact three-dimensional industrial measurement. In SV systems, camera orientation (the angles formed by the two cameras optical axes across the baseline) is among the factors that influence the measurement accuracy. Presently, there is a great divergence regarding the optimal value of camera orientation, i.e., existing theoretical analyses suggest that the optimal angle lies in 30 $^\circ$ –50 $^\circ$ ; however, a camera orientation angle between 60 $^\circ$ –80 $^\circ$ is typically used in practical SV systems and commercial products. Unlike previous models that treated system parameters as uncorrelated, the proposed model introduces covariance to model the correlation between camera orientation and the accuracy of detecting corresponding points. The proposed model proves the optimal camera orientation angle lies in 60 $^\circ$ –80 $^\circ$ , which was verified experimentally via measurements with a circle center tracker (CCT), fringe projection profilometry (FPP), and stereo digital image correlation (DIC).

中文翻译：

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低测量误差的立体视觉系统中的相机方向优化

立体视觉（SV）广泛用于非接触式三维工业测量。在SV系统中，相机方向（两个相机光轴在基线上形成的角度）是影响测量精度的因素之一。目前，关于相机方位的最佳值存在很大分歧，即现有的理论分析表明最佳角度在30 $ ^ \ circ $ –50 $ ^ \ circ $ ; 但是，相机的方位角介于60 $ ^ \ circ $ –80 $ ^ \ circ $通常用于实际的SV系统和商业产品。与先前的将系统参数视为不相关的模型不同，所提出的模型引入协方差来对摄像机方向与检测相应点的准确性之间的相关性进行建模。所提出的模型证明了相机的最佳方位角在60° $ ^ \ circ $ –80 $ ^ \ circ $ ，已通过使用圆心跟踪器（CCT），条纹投影轮廓图（FPP）和立体数字图像相关性（DIC）的测量进行了实验验证。