Multi-Camera 3D Digital Image Correlation with Pointwise-Optimized Model-Based Stereo Pairing

基于逐点优化模型的立体配对的多相机3D数字图像相关

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Abstract

Dynamic deformation measurement (DDM) is critical across infrastructure and industrial applications. Among various advanced techniques, multi-camera digital image correlation (MC-DIC) stands out due to its ability to achieve wide-range, full-field, and non-contact 3D DDM by pairing camera subsystems. However, existing MC-DIC methods typically rely on inefficient manual pairing or a simplistic strategy that aggregates all visible cameras for measuring specific object regions, leading to camera over-grouping. These limitations often result in cumbersome system setup and ill-measured deformations. To overcome these challenges, we propose a novel MC-DIC method with pointwise-optimized model-based stereo pairing (MPMC-DIC). By automatically evaluating and selecting camera pairs based on five evaluation factors derived from 3D model and calibrated cameras, the proposed method overcomes the over-grouping problem and achieves high-precision DDM of semi-rigid objects. A Ø5 × 5 cm cylinder experiment demonstrated an accuracy of 0.03 mm for both horizontal and depth displacements in the 0.0-5.0 mm range, and validated strong robustness against cluttered backgrounds using a 2 × 4 camera array. Vibration measurement of a 9 × 15 × 16 cm PC speaker operating at 50 Hz, using eight surrounding cameras capturing 1920 × 1080 images at 400 fps, confirmed the proposed method's capability to perform wide-range dynamic deformation analysis and its robustness against complex object geometries.

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