Automated UAV image-to-BIM registration for planar and curved building façades using structure-from-motion and 3D surface unwrapping

Texturing Building Information Model (BIM) with up-to-date Unmanned Aerial Vehicle (UAV) images has brought substantial benefits to building façade inspection. However, current image-to-BIM registration methods are sensitive to UAV positioning accuracy and façade features. Additionally, perspective and geometry distortions on UAV images hinder the texturing of curved façades. To address these issues, this paper introduces an approach to registering UAV images onto BIM for buildings with both planar and curved façades. Firstly, Structure-from-Motion is used to align UAV images with BIM. Secondly, fragmented and distorted UAV images of planar and curved façades are converted onto a distortion-free panoramic image using 3D surface unwrapping. Thirdly, the generated panoramic image is projected onto BIM surfaces as textures. The process has been automated using a Dynamo prototype and evaluated through computer simulation and a real-world case study. The outcome shows a mean accuracy of 1.7 pixels and 8.5 mm. • An UAV image-to-BIM registration framework accommodating both planar and curved building façades is proposed. • SfM is adopted to estimate the relative UAV image pose to BIM. • Perspective and geometry distortions on UAV images are corrected using BIM-based 3D surface unwrapping. • A distortion-free panoramic image is generated and textured onto BIM surfaces. • A Dynamo prototype is developed to automate the process in the framework.

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Publication Details

Journal
Automation in Construction
Published
2025-03-28
DOI
https://doi.org/10.1016/j.autcon.2025.106148
Citations
7
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
16.43
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article

Automated UAV image-to-BIM registration for planar and curved building façades using structure-from-motion and 3D surface unwrapping

Feng Wang, Johannes Dimyadi, Cheng Zhang, Yang Zou
7 citations
Automation in Construction
3D Surveying and Cultural Heritage
16.43
article

Automated UAV image-to-BIM registration for planar and curved building façades using structure-from-motion and 3D surface unwrapping

Feng Wang, Johannes Dimyadi, Cheng Zhang, Yang Zou
article en
7 citations

Abstract

Texturing Building Information Model (BIM) with up-to-date Unmanned Aerial Vehicle (UAV) images has brought substantial benefits to building façade inspection. However, current image-to-BIM registration methods are sensitive to UAV positioning accuracy and façade features. Additionally, perspective and geometry distortions on UAV images hinder the texturing of curved façades. To address these issues, this paper introduces an approach to registering UAV images onto BIM for buildings with both planar and curved façades. Firstly, Structure-from-Motion is used to align UAV images with BIM. Secondly, fragmented and distorted UAV images of planar and curved façades are converted onto a distortion-free panoramic image using 3D surface unwrapping. Thirdly, the generated panoramic image is projected onto BIM surfaces as textures. The process has been automated using a Dynamo prototype and evaluated through computer simulation and a real-world case study. The outcome shows a mean accuracy of 1.7 pixels and 8.5 mm. • An UAV image-to-BIM registration framework accommodating both planar and curved building façades is proposed. • SfM is adopted to estimate the relative UAV image pose to BIM. • Perspective and geometry distortions on UAV images are corrected using BIM-based 3D surface unwrapping. • A distortion-free panoramic image is generated and textured onto BIM surfaces. • A Dynamo prototype is developed to automate the process in the framework.

Automation in ConstructionVol. 174
University of Auckland (NZ)
Sustainable cities and communities
Openalex Percentile: Top 1%
3D Surveying and Cultural Heritage
16.43
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Automated UAV image-to-BIM registration for planar and curved building façades using structure-from-motion and 3D surface unwrapping — Feng Wang, Johannes Dimyadi, et al. · Automation in Construction (2025) | TGRS Research Map | TGRS