Frédéric Bosché

TL;DR: A new approach for automated recognition of project 3D Computer-Aided Design model objects in large laser scans is presented, with significant improvements compared to the one originally proposed in Bosche et al. (in press) [11].

TL;DR: The research presented in this paper combines the Hough transform and “Scan-vs-BIM” systems in a unified approach for more robust automated comparison of as-built and as-planned cylindrical MEP works, thereby providing the basis for automated earned value tracking, automated percent-built-as-planned measures, and assistance for the delivery of as -built BIM models from as-designed ones.

TL;DR: A novel system is described herein that combines 3D object recognition technology with schedule information into a combined 4D object oriented progress tracking system that demonstrates a degree of accuracy for automated progress tracking that meets or exceeds typical manual performance.

TL;DR: This paper presents a new approach for robust automated recognition/retrieval of 3D CAD objects in range point clouds in the Architectural/Engineering/Construction & Facility Management (AEC-FM) context and demonstrates how this approach can be used for efficiently assessing construction progress.

TL;DR: In this article, a Scan-vs-BIM object recognition framework was proposed for the automatic assessment of as-built status of MEP works in construction projects at a cost that continues to decline.