Three-dimensional reconstruction and segmentation of an aggregate stockpile for size and shape analyses

TL;DR

This paper introduces a mobile-friendly 3D imaging method using Structure-from-Motion to reconstruct and segment aggregate stockpiles, enabling on-site size and shape analysis for quality control in construction.

Contribution

It develops an innovative, affordable 3D reconstruction and segmentation system for aggregate stockpiles using smartphone images, facilitating field-based analysis.

Findings

Successful 3D surface reconstruction from smartphone videos

Effective segmentation of individual aggregates from the 3D point cloud

Demonstrated potential for onsite QA/QC applications

Abstract

Aggregate size and shape are key properties for determining quality of aggregate materials used in road construction and transportation geotechnics applications. The composition and packing, layer stiffness, and load response are all influenced by these morphological characteristics of aggregates. Many aggregate imaging systems developed to date only focus on analyses of individual or manually separated aggregate particles. There is a need to develop a convenient and affordable system for acquiring 3D aggregate information from stockpiles in the field. This paper presents an innovative 3D imaging approach for potential field evaluation of large-sized aggregates, whereby engineers can perform inspection by taking videos/images with mobile devices such as smartphone cameras. The approach leverages Structure-from-Motion (SfM) techniques to reconstruct the stockpile surface as 3D spatial data, i.e. point cloud, and uses a 3D segmentation algorithm to separate and extract individual aggregates from the reconstructed stockpile. The preliminary results presented in this paper demonstrate the future potential of using 3D aggregate size and shape information for onsite Quality Assurance/Quality Control (QA/QC) tasks.