Large-scale particle image velocimetry (LSPIV) has been widely used for quantifying the velocity distribution of environmental water surfaces, especially river flows. In LSPIV, the evaluated velocity distribution of a region far from the camera tends to have a large uncertainty due to strong image distortion and reduced image resolution, especially for directions parallel to the viewing angle. This study proposes a method that overcomes this problem by combining the results of LSPIV measurements of images obtained from different viewing angles. The velocity component for the direction orthogonal to the viewing angle (the 1D velocity component) for each viewing angle was extracted and then the 2D velocity field was reconstructed based on a least squares algorithm. To validate the proposed method, a rigid rotating disk experiment and a circulatory flow flume experiment were conducted. The method was used to reproduce a complex flow formed around an opposite river edge using images...

中文翻译：

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多摄像机大规模粒子图像测速

大规模粒子图像测速仪（LSPIV）已被广泛用于量化环境水面，尤其是河流流量的速度分布。在LSPIV中，由于强烈的图像失真和降低的图像分辨率（尤其是对于平行于视角的方向），所评估的远离相机的区域的速度分布往往具有较大的不确定性。这项研究提出了一种方法，可以通过组合从不同视角获得的图像的LSPIV测量结果来克服此问题。提取与每个视角正交的方向的速度分量（一维速度分量），然后基于最小二乘算法重建二维速度场。为了验证提出的方法，进行了刚性转盘实验和循环水槽实验。该方法用于再现利用图像生成的相对河流边缘周围形成的复杂流。