Abstract
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.
Highlights
Today, overpopulation and its concentration in the central nucleus of cities have led to more complex urban problems
The main contribution of this paper is to provide a projectionbased approach for automatic 3D reconstruction of the major elements of the bridge including the railing, body and abutment elements from photogrammetric point clouds
To segment the point cloud into the main bridge elements, required features including the height and spectral values, 3D density, normal vectors and planarity conditions are calculated for points in a one-meter neighborhood
Summary
Overpopulation and its concentration in the central nucleus of cities have led to more complex urban problems. 3D CAD models are an accurate data source to measure and update geometric and spatial information (Cabaleiro et al, 2016). In this regard, 3D models of the bridge structures, in addition to purposeful and comprehensive coverage of urban problems, are widely used in many applications such as highspeed monitoring and inspections (Zhang et al, 2014; Cheng et al, 2019; León et al, 2019), safety, crisis management, and transportation system. The main idea is to employ the geometric relations between the elements in different bridges as knowledge to reduce the geometrical and structural complexities during the modeling of bridges
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