3D Surface Reconstruction of Coarse Aggregate Particles from Occlusion-Free Multi-View Images

Abstract

Rapidly and accurately assessing the geometric characteristics of coarse aggregate particles is crucial for ensuring pavement performance in highway engineering. This article introduces an innovative system for the three-dimensional (3D) surface reconstruction of coarse aggregate particles using occlusion-free multi-view imaging. The system captures synchronized images of particles in free fall, employing a matte sphere and a nonlinear optimization approach to estimate the camera projection matrices. A pre-trained segmentation model is utilized to eliminate the background of the images. The Shape from Silhouettes (SfS) algorithm is then applied to generate 3D voxel data, followed by the Marching Cubes algorithm to construct the 3D surface contour. Validation against standard parts and diverse coarse aggregate particles confirms the method's high accuracy, with an average measurement precision of 0.434 mm and a significant increase in scanning and reconstruction efficiency.