Prospect of architectonic grammar reconstruction from dense 3D point clouds: Historical building information modeling (HBIM) of Guangdong cultural heritages

Abstract

Building information modeling (BIM) of cultural heritages, i.e., historic building information modeling (HBIM), advances the monitoring, maintenance, restoration, and virtual exhibitions of historical buildings. However, due to the elaborate styles and the unavoidable erosion and renovation, the reconstruction of HBIM from the prevalent raw data, such as point clouds and images, is very challenging, especially parametrical and semantic modeling. Recent studies have noticed the potential of architectonic grammar for facilitating parametric and semantic reconstruction. In this paper, we investigate the manual modeling of cultural heritage with the architectonic grammar and propose a roadmap consisting of four levels of automation, i.e., ‘calibration,’ ‘selection,’ ‘combination,’ and ‘generation,’ of the architectonic grammar reconstruction. Further quality improvement and cost analysis of these four levels show that ‘calibration’ and ‘selection’ are the most suitable options currently for real-world applications. This study inspires the future application of architectonic grammar to facilitate the parametric and semantic HBIM reconstruction and explores the prospect of a new HBIM reconstruction schema.