Near-real-time 3D point cloud generation and anomaly detection for excavated slope using SfM-MVS

Abstract

This study targets safety management at slope-excavation sites and, with digital-twin applications in mind, proposes a near-real-time, non-contact method for capturing areal displacements through 3-D point-cloud generation and anomaly detection. An operational workflow was built and its feasibility examined for two SfM-MVS configurations that convert interval photographs from fixed cameras into point clouds: (1) COLMAP + openMVS and (2) Agisoft Metashape. Aligned point clouds for each epoch were generated in 162 s and 183 s, respectively, enabling continuous, high-density updates with a delay of roughly three minutes. Temporal point-cloud differences were transformed into depth images, and pixel-wise differencing over time visualized and quantified precursory deformation, confirming the effectiveness of automated anomaly detection. Compared with conventional sensor-based monitoring, the method provides comprehensive areal displacement information.