Intelligent Digital Built Heritage Models: An Approach from Image Processing and Building Information Modelling Technology

Author(s)

de Paiva, Pedro V. V. ; Cogima, Camila K. ; Dezen-Kempter, Eloisa ; de Carvalho, Marco A. G. ; Cerqueira, Lucas R. ; Tremeau, A ; Imai, F ; Braz, J

• Document type: Journal article
• Source: VISAPP: PROCEEDINGS OF THE 13TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS - VOL 4: VISAPP; v. N/A, p. 8-pg., 2018-01-01.

Abstract

Conservation and maintenance of historic buildings have exceptional requirements and need a detailed diagnosis and an accurate as-is documentation. This paper reports the use of Unmanned Aerial Vehicle (UAV) imagery to create an Intelligent Digital Built HeritageModel (IDBHM) based on Building Information Modeling (BIM) technology. Our work outlines a model-driven approach based on UAV data acquisition, photogrammetry, post-processing and segmentation of point clouds to promote partial automation of BIM modeling process. The methodology proposed was applied to a historical building facade located in Brazil. A qualitative and quantitative assessment of the proposed segmentation method was undertaken through the comparison between segmented clusters and as-designed documents, also as between point clouds and ground control points. An accurate and detailed parametric IDBHM was created from high-resolution Dense Surface Model (DSM). This Model can improve conservation and rehabilitation works. The results demonstrate that the proposed approach yields good results in terms of effectiveness in the clusters segmentation, compared to the as-designed model. (AU)

• FAPESP's process: 17/02787-9 - A framework to integrate multi-sensors data with building information modeling to support historic assets conservation and management
• Grantee: Pedro Victor Vieira de Paiva
• Support Opportunities: Scholarships in Brazil - Master
• FAPESP's process: 16/04991-0 - A framework to integrate multi-sensors data with building information modeling to support historic assets conservation and management
• Grantee: Eloisa Dezen-Kempter
• Support Opportunities: Research Grants - eScience and Data Science Program - Regular Program Grants