Development of a Camera Localization System for Three-Dimensional Digital Image Correlation Camera Triangulation

Advancements in computer-vision methods have made stereophotogrammetry and three-dimensional digital image correlation (3D-DIC) attractive tools for Structural Health Monitoring (SHM). Nonetheless, optical approaches are not always well suited for quantitative measurement on large-scale structures d...

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Bibliographic Details
Published inIEEE sensors journal Vol. 20; no. 19; pp. 11518 - 11526
Main Authors Sabato, Alessandro, Valente, Nicholas A., Niezrecki, Christopher
Format Journal Article
LanguageEnglish
Published New York IEEE 01.10.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Calibration
Cameras
digital image correlation
Digital imaging
inertial measurement unit
Inertial platforms
MEMS
Monitoring
Parameters
Pitch (inclination)
Radar
Rolling motion
Sensor systems
Sensors
Stereophotogrammetry
Structural health monitoring
Three-dimensional displays
Triangulation
Yaw
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Summary:Advancements in computer-vision methods have made stereophotogrammetry and three-dimensional digital image correlation (3D-DIC) attractive tools for Structural Health Monitoring (SHM). Nonetheless, optical approaches are not always well suited for quantitative measurement on large-scale structures due to the challenging calibration process of the cameras. In this study, a novel multi-sensor system is presented to compute the stereophotogrammetry system's extrinsic parameters. This system can extend 3D-DIC's capability and allow for easier calibration and measurement. The proposed system integrates a MEMS-based Inertial Measurement Unit (IMU) for determining the spatial orientation of the cameras (i.e., roll, pitch, and yaw angles) and a 77 GHz radar sensor for measuring the relative distance of the stereo cameras. The prototype's effectiveness is evaluated through laboratory and analytical tests. Its accuracy in calculating the extrinsic parameters of a stereophotogrammetry system is demonstrated by direct comparison with data obtained from a traditional calibration. Results show that the multi-sensor system can determine the separation angle between the two cameras with an error below 2% when the comparison is made.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2020.2997774