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Advanced-Technological UAVs-Based Enhanced Reconstruction of Edges for Building Models
Accurate building models are widely used in the construction industry in the digital era. UAV cameras combined with image-based reconstruction provide a low-cost technology for building modeling. Most existing reconstruction methods operate on point clouds, while massive points reduce computational efficiency, and the accumulated error of point position often distorts building edges. This paper introduces an innovative 3D reconstruction method, Edge3D, that recovers building edges in the form of 3D lines. It employs geometry constraints and progressive screening technology to improve the robustness and precision of line segment matching. An innovative bundle adjustment strategy based on endpoints is designed to reduce the global reprojection error. Edges were tested on challenging real-world image sets, and matching precisions of 96% and 94% were achieved on the two image sets, respectively, with good reconstruction results. The proposed approach reconstructs building edges using a small number of lines instead of massive points, which contributes to the rapid reconstruction of building contour construction and obtaining accurate models, serving as an important foundation for the promotion of construction advancement.
Advanced-Technological UAVs-Based Enhanced Reconstruction of Edges for Building Models
Accurate building models are widely used in the construction industry in the digital era. UAV cameras combined with image-based reconstruction provide a low-cost technology for building modeling. Most existing reconstruction methods operate on point clouds, while massive points reduce computational efficiency, and the accumulated error of point position often distorts building edges. This paper introduces an innovative 3D reconstruction method, Edge3D, that recovers building edges in the form of 3D lines. It employs geometry constraints and progressive screening technology to improve the robustness and precision of line segment matching. An innovative bundle adjustment strategy based on endpoints is designed to reduce the global reprojection error. Edges were tested on challenging real-world image sets, and matching precisions of 96% and 94% were achieved on the two image sets, respectively, with good reconstruction results. The proposed approach reconstructs building edges using a small number of lines instead of massive points, which contributes to the rapid reconstruction of building contour construction and obtaining accurate models, serving as an important foundation for the promotion of construction advancement.
Advanced-Technological UAVs-Based Enhanced Reconstruction of Edges for Building Models
Luping Li (author) / Jian Chen (author) / Xing Su (author) / Ahsan Nawaz (author)
2022
Article (Journal)
Electronic Resource
Unknown
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