Abstract

This paper presents a projection-based method for 3D bridge modeling using dense point clouds generated from drone-based images. The proposed workflow consists of hierarchical steps including point cloud segmentation, modeling of individual elements, and merging of individual models to generate the final 3D model. First, a fuzzy clustering algorithm including the height values and geometrical-spectral features is employed to segment the input point cloud into the main bridge elements. In the next step, a 2D projection-based reconstruction technique is developed to generate a 2D model for each element. Next, the 3D models are reconstructed by extruding the 2D models orthogonally to the projection plane. Finally, the reconstruction process is completed by merging individual 3D models and forming an integrated 3D model of the bridge structure in a CAD format. The results demonstrate the effectiveness of the proposed method to generate 3D models automatically with a median error of about 0.025 m between the elements’ dimensions in the reference and reconstructed models for two different bridge datasets.

Details

Title
A PROJECTION-BASED RECONSTRUCTION ALGORITHM FOR 3D MODELING OF BRIDGE STRUCTURES FROM DRONE-BASED POINT CLOUD
Author
Mehranfar, M 1 ; Arefi, H 2 ; Alidoost, F 3 

 School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Iran; School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Iran 
 School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Iran; School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Iran; School of Technology, Department of Geoinformatics and Surveying, Mainz University of Applied Sciences, Germany 
 Faculty of Geomatics, Computer Science and Mathematics, Stuttgart University of Applied Sciences, Germany; Faculty of Geomatics, Computer Science and Mathematics, Stuttgart University of Applied Sciences, Germany 
Pages
77-83
Publication year
2021
Publication date
2021
Publisher
Copernicus GmbH
ISSN
16821750
e-ISSN
21949034
Source type
Conference Paper
Language of publication
English
ProQuest document ID
2585327750
Copyright
© 2021. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.