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Three-dimensional (3D) reconstruction based on digital speckle correlation has gained widespread usage in dynamic scenarios due to its ability to achieve single-frame reconstruction. Traditional binocular speckle structured light systems often face challenges such as insufficient surface texture richness and excessive curvature, leading to limitations in the accuracy of corresponding point localization during the matching process. Furthermore, partial point cloud loss caused by varying viewpoints can impact the precision and completeness of 3D reconstruction. This paper introduces a Multiview speckle correlation-based approach for 3D reconstruction. By establishing multi-view stereo camera epipolar rectification, complex speckle matching issues are transformed into one-dimensional searches along unified epipolar lines, simplifying the matching process and enhancing efficiency. Additionally, a digital speckle correlation computational model and subpixel interpolation algorithm based on Newton-Raphson iteration are employed to realize multi-view subpixel-level corresponding point localization. Ultimately, the reconstruction point cloud data is obtained through the intersection of three-ray least squares method. Experimental results demonstrate that this method achieves higher accuracy and better model completeness in 3D data reconstruction.
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