This study proposes a motion-compensation vision measurement method and system for structural displacement, termed the parallel camera network (PCN). Based on the fixedly connected calibration cameras and measurement cameras, the PCN method effectively address the optical measurement problems of the unstable observation platform. Unlike existing ego-motion compensation methods, the PCN method allows for reference or stationary points that are distant from the camera stations, significantly reducing motion-induced measurement errors of the observation platform. Laboratory tests showed that compensating for platform motion tripled measurement accuracy using the PCN method. In practical applications, the system has been successfully deployed for monitoring subsidence of operational high-speed rail piers and the arch axis during large-span arch bridge construction. The proposed method and system significantly enhance the engineering flexibility of visual measurements.

中文翻译：

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并行相机网络：结构位移运动补偿视觉测量方法及系统


本研究提出了一种用于结构位移的运动补偿视觉测量方法和系统，称为并行相机网络（PCN）。 PCN方法基于固定连接的标定相机和测量相机，有效解决了不稳定观测平台的光学测量问题。与现有的自运动补偿方法不同，PCN 方法允许远离摄像机站的参考点或静止点，从而显着减少观察平台运动引起的测量误差。实验室测试表明，使用 PCN 方法补偿平台运动使测量精度提高了三倍。在实际应用中，该系统已成功应用于大跨拱桥施工过程中运营高铁桥墩和拱轴的沉降监测。所提出的方法和系统显着增强了视觉测量的工程灵活性。