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Uncertainty and accuracy of vision-based tracking concerning stereophotogrammetry and noise-floor tests

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This work proposes a systematic assessment of stereophotogrammetry and noise-floor tests to characterize and quantify the uncertainty and accuracy of a vision-based tracking system. Two stereophotogrammetry sets with different configurations, i.e., some images are designed and their sensitivity is quantified based on several assessments. The first assessment evaluates the image coordinates, stereo angle and reconstruction errors resulting from the stereophotogrammetry procedure, and the second assessment expresses the uncertainty from the variance and bias errors measured from the noise-floor test. These two assessments quantify the uncertainty, while the accuracy of the vision-based tracking system is assessed from three quasi-static tests on a small-scaled specimen. The difference in each stereophotogrammetry set and configuration, as indicated by the stereophotogrammetry and noise-floor assessment, leads to a significant result hat the first stereophotogrammetry set measures the RMSE of 3.6 mm while the second set identifies only 1.6 mm of RMSE. The results of this work recommend a careful and systematic assessment of stereophotogrammetry and noise-floor test results to quantify the uncertainty before the real test to achieve a high displacement accuracy of the vision-based tracking system.
Rocznik
Strony
75--92
Opis fizyczny
Bibliogr. 37 poz., rys., tab., wykr., wzory
Twórcy
  • University of Nevada, Department of Civil & Environmental Engineering, Reno, NV 89557, USA
  • Research Center for Biomaterials, National Research and Innovation Agency, Cibinong Science Center, Jl. Raya Bogor km 46, Cibinong, 16911, Indonesia
  • University of Nevada, Department of Civil & Environmental Engineering, Reno, NV 89557, USA
Bibliografia
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Uwagi
1. The authors would like to thank the Los Alamos National Laboratory for providing funding for the vison-based system upgrade and validation tests in this study. We like to thank Sherif Elfass Ph.D. for valuable insight on the validation tests, and Tim Schmidt of Trilion Quantity Systems, USA for the technical support on various aspects of the system hardware and software.
2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4e45d658-f00c-493d-b490-7e7fae5af529
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