A homography transformation based video stabilization method for structural health monitoring using a unmanned aerial vehicle

Miaoshuo Li, Fengshou Gu, Andrew Ball, Lin Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Using a computer vision technique to perform vibration-based structural health monitoring has advantages in that it is a low-cost non-contact approach, thus attracting a lot of attention. Great progress has been made recently. However, it is difficult for static cameras to be placed in an effective location in many scenarios, such as monitoring large-scale wind turbines, bridges, etc. The unmanned aerial vehicle (UAV) is a good choice to deal with this issue. In the past ten years, the application of UAVs in structural health monitoring was increasing dramatically. However, the non-stationary motion of a hovering UAV is a great challenge in terms of the estimation of dynamic characteristics. Thus, it is important to stabilise the video to achieve the level at which vibration can be monitored.
This paper puts forward a video stabilisation method based on homography transformation for the purpose of applying UAVs to vision-based vibration monitoring. Firstly, a motion model is built between the motion of the camera, called ego-motion, and its displacement on film. Secondly, an experiment is conducted to define the characteristics of a hovering UAV’s ego-motion. Thirdly, a stabilisation algorithm is developed for the compensation of ego-motion.
Original languageEnglish
Title of host publicationSixteenth International Conference on Condition Monitoring and Asset Management (CM 2019)
PublisherBritish Institute of Non-Destructive Testing
Volume1
ISBN (Print)9781510889774
Publication statusPublished - 1 Aug 2019
EventSixteenth International Conference on Condition Monitoring and Asset Management - Glasgow, United Kingdom
Duration: 25 Jun 201927 Jun 2019
Conference number: 16
https://www.bindt.org/events/CM2019/ (Conference website. )

Conference

ConferenceSixteenth International Conference on Condition Monitoring and Asset Management
Abbreviated titleCM 2019
CountryUnited Kingdom
CityGlasgow
Period25/06/1927/06/19
Internet address

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  • Cite this

    Li, M., Gu, F., Ball, A., & Song, L. (2019). A homography transformation based video stabilization method for structural health monitoring using a unmanned aerial vehicle. In Sixteenth International Conference on Condition Monitoring and Asset Management (CM 2019) (Vol. 1). [130] British Institute of Non-Destructive Testing.