Hierarchical Dense Structure-from-Motion Reconstructions for Infrastructure Condition Assessment

Accurate condition assessment of in-service infrastructure systems is critical for system-wide prioritization decisions. Current protocols require lengthy inspections and expensive equipment to examine large infrastructure systems. Furthermore, changes in inspection protocols over time can create discontinuities in recording and understanding the time history of a structure. To address these challenges, a systematic and adaptive technique for converting two-dimensional (2D) digital images into three-dimensional (3D) models has been developed, with the goal of creating high-resolution and scale-accurate inspection records. The developed reconstruction technique utilizes multiscale imaging to reconstruct a structure with varying levels of details and geometric complexity. The captured images are then converted into photorealistic, accurate, and dense 3D scene reconstructions by utilizing a hierarchical adaptation of a dense structure-from-motion (DSfM) algorithm. The result of this approach is a virtual 3D model of the structure with accurate geometry and high-fidelity representation of fine details. The accuracy, completeness, adaptability, and feasibility of the developed method were compared to both terrestrial laser scanner (TLS) and conventional DSfM methods. Experimental findings and direct comparison between generated point clouds indicate that the developed hierarchical technique consistently produces dense point clouds capable of resolving 0.1-mm details, an order of magnitude improvement over existing methods. The developed technique also allows for user-controlled point cloud density, a significant benefit over current reconstruction methods. (C) 2016 American Society of Civil Engineers.