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Smart Structures and Systems
  Volume 30, Number 5, November 2022 , pages 501-511

Deep learning approach to generate 3D civil infrastructure models using drone images
Ji-Hye Kwon, Shekhroz Khudoyarov, Namgyu Kim and Jun-Haeng Heo

    Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.
Key Words
    automatic model generation; deep learning algorithm; noise reduction; point cloud; semantic segmentation
(1) Ji-Hye Kwon, Jun-Haeng Heo:
School of Civil and Environmental Engineering, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Republic of Korea;
(2) Shekhroz Khudoyarov:
SISTech Co., LTD, 209, Neungdong-ro, Gwangjin-gu, Seoul, 05006, Republic of Korea;
(3) Namgyu Kim:
Research Strategic Planning Department, Korea Institute of Civil Engineering and Building Technology, 283, Goyangdae-Ro, Ilsanseo-Gu, Goyang-Si, Gyeonggi-Do, 10223, Republic of Korea.

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