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A robust matching method for fast 3D shape measurement using digital speckle correlation

机译:一种利用数字散斑相关性快速3D形测量的强大匹配方法

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Digital speckle correlation (DSC) solves the problem of searching corresponding points between two images, and it shows great application potential in pattern-projection based fast 3D shape measurement, because only one shot is enough to retrieve the 3D structure. As DSC relies on analyzing the spatial intensity distribution of a subset in image with a given point, it is likely to get false correspondences in low quality DSC area such as the background, because the searching range is hard to locate. So it is still hard to use DSC to realize fast 3D shape measurement. To solve this problem, the gray standard deviation of the subset is designed to recognize and remove the low-quality DSC area, and the principle of epipolar geometry and disparity constraint are utilized to determine the searching range, so the correspondences can be obtained. Moreover, in order to enhance the robustness of this method, a connected region method based on neighboring pixels possessing similar disparity is proposed to remove mismatched points after establishing initial disparity map by correspondences. Once the disparity map is obtained 3D structure can be retrieved based on the triangulation principle. The experiment on reconstructing Gorky plaster statue is performed, verifying that the proposed method can substantially reduce mismatched points and achieve robust single frame 3D shape measurement.
机译:数字散斑相关性(DSC)解决了在两个图像之间搜索对应点的问题,并且它在基于模式投影的快速3D形状测量中显示出很大的应用势,因为只有一个镜头足以检索3D结构。由于DSC依赖于通过给定点分析图像中的子集的空间强度分布,因此可能会在诸如背景之类的低质量DSC区域中获得假对应,因为搜索范围很难定位。因此,仍然很难使用DSC来实现快速的3D形状测量。为了解决这个问题,子集的灰色标准偏差被设计为识别和去除低质量的DSC区域,并且利用末极几何和视差约束的原理来确定搜索范围,因此可以获得对应关系。此外,为了提高该方法的鲁棒性,提出了基于具有类似视差的相邻像素的连接区域方法以在通过对应关系建立初始视差图之后除去错配点。一旦获得了视差图,可以基于三角测量原理检索3D结构。进行重建Gorky石膏雕像的实验,验证所提出的方法可以大大减少错配点并实现鲁棒单帧3D形状测量。

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