2017 conference paper

Perspective-based image-to-bim alignment for automated visual data collection and construction performance monitoring

Computing in Civil Engineering 2017: Sensing, Simulation, and Visualization, 171–178.

By: K. Boroujeni & K. Han n 

co-author countries: United States of America πŸ‡ΊπŸ‡Έ
Source: NC State University Libraries
Added: August 6, 2018

In efforts to automate construction performance monitoring, past studies have worked on vision-based registration of image to BIM and 3D point clouds to BIM. The continuous development of simultaneous localization and mapping (SLAM) enabled real-time estimation of locations and orientations of a camera while incrementally reconstructing a 3D scene. However, it localizes a camera to an arbitrary local coordinate system and produces a low-resolution and noisy point cloud that is not suitable for quality assessment of a structure. For the architecture/engineering/construction industry, the better and realistic approach is to localize with respect to building information models (BIMs) in real-time and post-process 3D dense reconstruction. This approach will allow project management teams to better communicate quality and progress using visuals associated with locations shown with BIMs. Moreover, it will automate images-to-BIM and image-based point clouds-to-BIM registration, enhancing past studies that attempt to automate image-based progress detection and quality assessment. On the other hand, the current state-of-the-art method for registering an image-based point cloud to a BIM requires selection of the correspondences. To address these challenges and achieve automation, this paper presents a new localization method that aligns an image to a BIM by detecting and matching perspectives of the image and the BIM. The results demonstrate the potential for enabling automated visual data collection (as-built aligned with as-planned) for performance monitoring.