Benutzer: Gast  Login
Titel:

Change detection for indoor construction progress monitoring based on BIM, point clouds and uncertainties

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Meyer, Theresa; Brunn, Ansgar; Stilla, Uwe
Abstract:
Automatic construction progress documentation and metric evaluation of execution work in confined building interiors requires particularly reliable geometric evaluation and interpretation of statistically uncertain as-built point clouds. This paper presents a method for high-resolution change detection based on dense 3D point clouds from terrestrial laser scanning (TLS) and the discretization of space by voxels. In order to evaluate the metric accuracy of a BIM according to the Level of Accuracy...     »
Stichworte:
Change detection, Uncertainty, BIM, 3D point clouds, Evidence theory, LOCenter, LOCTop_Data_Generation_and_Object_Reconstruction
Zeitschriftentitel:
Automation in Construction
Jahr:
2022
Band / Volume:
141
Seitenangaben Beitrag:
104442
Volltext / DOI:
doi:https://doi.org/10.1016/j.autcon.2022.104442
WWW:
https://www.sciencedirect.com/science/article/pii/S0926580522003156
Print-ISSN:
0926-5805
Semester:
SS 22
 BibTeX