Application Status and Prospect on Computer Vision Technology Application in Bridge and Tunnel Engineering

YANG Xingyu; CHEN Guangyao; ZHU Juntong; XU Zhao

doi:10.3724/j.gyjzG23051209

Volume 54 Issue 9

Sep. 2024

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Article Navigation > INDUSTRIAL CONSTRUCTION > 2024 > 54(9): 209-218

Sun Jianping, Chen Qihui, Bai Hongyu, Zhu Jian, Wang Mingbo. ANALYSIS AND TREATMENT FOR INCLINATION OF RESIDENTIAL BUILDING[J]. INDUSTRIAL CONSTRUCTION, 2005, 35(11): 97-99. doi: 10.13204/j.gyjz200511029

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YANG Xingyu, CHEN Guangyao, ZHU Juntong, XU Zhao. Application Status and Prospect on Computer Vision Technology Application in Bridge and Tunnel Engineering[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(9): 209-218. doi: 10.3724/j.gyjzG23051209

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Application Status and Prospect on Computer Vision Technology Application in Bridge and Tunnel Engineering

doi: 10.3724/j.gyjzG23051209

1. School of Civil Engineering, Southeast University, Nanjing 211189, China;
2. Department of Software, Southeast University, Suzhou 215000, China

Received Date: 2023-05-12
Available Online: 2024-10-18

Abstract

Abstract

Bridge and tunnel engineering is an important branch in the field of civil engineering. With the increasing digitization of construction and upgrades in hardware equipment, computer vision has become a key technology supporting the digital development of bridge and tunnel engineering. To comprehensively reveal the research hotspots and trends of computer vision in the field of bridge and tunnel engineering, the paper focused on the application of computer vision in bridge and tunnel engineering, used knowledge graph tools to conduct visualized analysis of relevant literature, and systematically summarized the theoretical and applied technologies of computer vision tasks, including image processing and feature extraction, object detection and tracking, object classification and recognition, 3D reconstruction and SLAM, and intelligent analysis and decision-making. Based on this, the paper also summarized the current research difficulties from four aspects: dataset defects, image accuracy, detection real-time performance, and algorithm applicability. The paper also identified and discussed solutions to application difficulties and provided prospects for future development, so as to provide theoretical support for further research and technological application.
- computer vision,
- bridge and tunnel construction,
- project management,
- information technology,
- construction technology

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References

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