This paper introduces a new accelerating algorithm, efficient match slimmer (EMS), specifically designed to lighten computational loads of sophisticated template matching algorithms, enabling these algorithms to be effectively run on single-board computers. Utilizing EMS in conjunction with a robust template matching algorithm, we have developed Raspberry Vision—a compact, cost-effective, and real-time vision-based system. Its compactness and portability facilitate a practical measurement strategy that not only minimizes the camera-to-target distance but also simplifies the camera calibration process in bridge displacement monitoring, thereby enhancing measurement accuracy. The performance of the system is estimated on two operational suspension bridges. The results demonstrate that Raspberry Vision, equipped with the measurement strategy, can significantly improve the measurement accuracy in the long-span bridge test and is also suitable for cross-sea bridge measurements.

中文翻译：

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使用具有速度优化模板匹配功能的紧凑型视觉系统对大跨度桥梁进行实时位移测量


本文介绍了一种新的加速算法，即高效匹配精简器（EMS），专门用于减轻复杂模板匹配算法的计算负载，使这些算法能够在单板计算机上有效运行。利用 EMS 与强大的模板匹配算法相结合，我们开发了 Raspberry Vision——一种紧凑、经济高效、基于视觉的实时系统。其紧凑性和便携性促进了实用的测量策略，不仅最小化了相机到目标的距离，还简化了桥梁位移监测中的相机校准过程，从而提高了测量精度。该系统的性能是在两座运行的悬索桥上进行评估的。结果表明，配备该测量策略的Raspberry Vision可以显着提高大跨桥梁测试的测量精度，也适用于跨海桥梁测量。