A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
From 3D point clouds to HBIM: Application of Artificial Intelligence in Cultural Heritage
Abstract Interest in semantic segmentation of 3D point clouds using ML and DL has grown due to their key role in scene insight across a wide range of computer vision, robotics and remote sensing applications. In the domain of Cultural Heritage, 3D point clouds are increasingly used as the backbone for as-built BIM models becoming a conventional approach to design in the AEC industry. However, there's a research gap in this field regarding the interface between point cloud segmentation and the HBIM workflow: there are no consistent studies demonstrating the possibility of automating the construction of parametric historical features from the segmentation process results in terms of geometry and semantic labels. The current research intends to perform a systematic review of the current bibliography with the aim of offering a constructive synthesis that will provide as a springboard for the advancement of innovative strategies in the field of BIM and AI.
Highlights Gap in the automation of BIM modelling concerning complex geometries belonging to the Historical Heritage. Automation of BIM modelling processes based on point clouds using Artificial Intelligence. The Scan to BIM workflow currently remains a time-consuming and erroneous manual process. What gaps need to be filled for an effective application of BIM in the field of Cultural Heritage?
From 3D point clouds to HBIM: Application of Artificial Intelligence in Cultural Heritage
Abstract Interest in semantic segmentation of 3D point clouds using ML and DL has grown due to their key role in scene insight across a wide range of computer vision, robotics and remote sensing applications. In the domain of Cultural Heritage, 3D point clouds are increasingly used as the backbone for as-built BIM models becoming a conventional approach to design in the AEC industry. However, there's a research gap in this field regarding the interface between point cloud segmentation and the HBIM workflow: there are no consistent studies demonstrating the possibility of automating the construction of parametric historical features from the segmentation process results in terms of geometry and semantic labels. The current research intends to perform a systematic review of the current bibliography with the aim of offering a constructive synthesis that will provide as a springboard for the advancement of innovative strategies in the field of BIM and AI.
Highlights Gap in the automation of BIM modelling concerning complex geometries belonging to the Historical Heritage. Automation of BIM modelling processes based on point clouds using Artificial Intelligence. The Scan to BIM workflow currently remains a time-consuming and erroneous manual process. What gaps need to be filled for an effective application of BIM in the field of Cultural Heritage?
From 3D point clouds to HBIM: Application of Artificial Intelligence in Cultural Heritage
Cotella, Victoria Andrea (author)
2023-05-11
Article (Journal)
Electronic Resource
English
Implementing HBIM on conservation heritage projects
| Emerald Group Publishing | 2020