Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring

Research output: Contribution to journalArticleResearchpeer review

Authors

  • Mohammad Omidalizarandi
  • Boris Kargoll
  • Jens-André Paffenholz
  • Ingo Neumann

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Original languageEnglish
Pages (from-to)105-134
Number of pages30
JournalJournal of Applied Geodesy
Volume13
Issue number2
Early online date2 Feb 2019
Publication statusPublished - 26 Apr 2019

Abstract

In the last two decades, the integration of a terrestrial laser scanner (TLS) and digital photogrammetry, besides other sensors integration, has received considerable attention for deformation monitoring of natural or man-made structures. Typically, a TLS is used for an area-based deformation analysis. A high-resolution digital camera may be attached on top of the TLS to increase the accuracy and completeness of deformation analysis by optimally combining points or line features extracted both from three-dimensional (3D) point clouds and captured images at different epochs of time. For this purpose, the external calibration parameters between the TLS and digital camera needs to be determined precisely. The camera calibration and internal TLS calibration are commonly carried out in advance in the laboratory environments. The focus of this research is to highly accurately and robustly estimate the external calibration parameters between the fused sensors using signalised target points. The observables are the image measurements, the 3D point clouds, and the horizontal angle reading of a TLS. In addition, laser tracker observations are used for the purpose of validation. The functional models are determined based on the space resection in photogrammetry using the collinearity condition equations, the 3D Helmert transformation and the constraint equation, which are solved in a rigorous bundle adjustment procedure. Three different adjustment procedures are developed and implemented: (1) an expectation maximization (EM) algorithm to solve a Gauss-Helmert model (GHM) with grouped t-distributed random deviations, (2) a novel EM algorithm to solve a corresponding quasi-Gauss-Markov model (qGMM) with t-distributed pseudo-misclosures, and (3) a classical least-squares procedure to solve the GHM with variance components and outlier removal. The comparison of the results demonstrates the precise, reliable, accurate and robust estimation of the parameters in particular by the second and third procedures in comparison to the first one. In addition, the results show that the second procedure is computationally more efficient than the other two.

Keywords

    adaptive robust estimation, digital camera, expectation maximisation algorithm, external calibration, Gauss-Helmert model, quasi-Gauss-Markov model, structural monitoring, Terrestrial laser scanner

ASJC Scopus subject areas

Cite this

Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring. / Omidalizarandi, Mohammad; Kargoll, Boris; Paffenholz, Jens-André et al.
In: Journal of Applied Geodesy, Vol. 13, No. 2, 26.04.2019, p. 105-134.

Research output: Contribution to journalArticleResearchpeer review

Omidalizarandi, M, Kargoll, B, Paffenholz, J-A & Neumann, I 2019, 'Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring', Journal of Applied Geodesy, vol. 13, no. 2, pp. 105-134. https://doi.org/10.1515/jag-2018-0038
Omidalizarandi, M., Kargoll, B., Paffenholz, J.-A., & Neumann, I. (2019). Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring. Journal of Applied Geodesy, 13(2), 105-134. https://doi.org/10.1515/jag-2018-0038
Omidalizarandi M, Kargoll B, Paffenholz JA, Neumann I. Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring. Journal of Applied Geodesy. 2019 Apr 26;13(2):105-134. Epub 2019 Feb 2. doi: 10.1515/jag-2018-0038
Omidalizarandi, Mohammad ; Kargoll, Boris ; Paffenholz, Jens-André et al. / Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring. In: Journal of Applied Geodesy. 2019 ; Vol. 13, No. 2. pp. 105-134.
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abstract = "In the last two decades, the integration of a terrestrial laser scanner (TLS) and digital photogrammetry, besides other sensors integration, has received considerable attention for deformation monitoring of natural or man-made structures. Typically, a TLS is used for an area-based deformation analysis. A high-resolution digital camera may be attached on top of the TLS to increase the accuracy and completeness of deformation analysis by optimally combining points or line features extracted both from three-dimensional (3D) point clouds and captured images at different epochs of time. For this purpose, the external calibration parameters between the TLS and digital camera needs to be determined precisely. The camera calibration and internal TLS calibration are commonly carried out in advance in the laboratory environments. The focus of this research is to highly accurately and robustly estimate the external calibration parameters between the fused sensors using signalised target points. The observables are the image measurements, the 3D point clouds, and the horizontal angle reading of a TLS. In addition, laser tracker observations are used for the purpose of validation. The functional models are determined based on the space resection in photogrammetry using the collinearity condition equations, the 3D Helmert transformation and the constraint equation, which are solved in a rigorous bundle adjustment procedure. Three different adjustment procedures are developed and implemented: (1) an expectation maximization (EM) algorithm to solve a Gauss-Helmert model (GHM) with grouped t-distributed random deviations, (2) a novel EM algorithm to solve a corresponding quasi-Gauss-Markov model (qGMM) with t-distributed pseudo-misclosures, and (3) a classical least-squares procedure to solve the GHM with variance components and outlier removal. The comparison of the results demonstrates the precise, reliable, accurate and robust estimation of the parameters in particular by the second and third procedures in comparison to the first one. In addition, the results show that the second procedure is computationally more efficient than the other two.",
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