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Title: Unmanned aerial vehicle-based computer vision for structural vibration measurement and condition assessment : a concise survey
Authors: Zhou, K
Wang, Z
Ni, YQ 
Zhang, Y
Tang, J
Issue Date: Jun-2023
Source: Journal of infrastructure intelligence and resilience, June 2023, v. 2, no. 2, 100031
Abstract: With the rapid advance in camera sensor technology, the acquisition of high-resolution images or videos has become extremely convenient and cost-effective. Computer vision that extracts semantic knowledge directly from digital images or videos, offers a promising solution for non-contact and full-field structural vibration measurement and condition assessment. Unmanned aerial vehicles (UAVs), also known as flying robots or drones, are being actively developed to suit a wide range of applications. Taking advantage of its excellent mobility and flexibility, camera-equipped UAV systems can facilitate the use of computer vision, thus enhancing the capacity of the structural condition assessment. The current article aims to provide a concise survey of the recent progress and applications of UAV-based computer vision in the field of structural dynamics. The different aspects to be discussed include the UAV system design and algorithmic development in computer vision. The main challenges, future trends, and opportunities to advance the technology and close the gap between research and practice will also be stated.
Keywords: Camera systems
Computer vision
Condition assessment
Unmanned aerial vehicles (UAVs)
Vibration measurement
Publisher: Elsevier Ltd
Journal: Journal of infrastructure intelligence and resilience 
EISSN: 2772-9915
DOI: 10.1016/j.iintel.2023.100031
Rights: © 2023 The Author(s). Published by Elsevier Ltd on behalf of Zhejiang University and Zhejiang University Press Co., Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
The following publication Zhou, K., Wang, Z., Ni, Y.-Q., Zhang, Y., & Tang, J. (2023). Unmanned aerial vehicle-based computer vision for structural vibration measurement and condition assessment: A concise survey. Journal of Infrastructure Intelligence and Resilience, 2(2), 100031 is available at https://doi.org/10.1016/j.iintel.2023.100031.
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