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      Review of Calibration Methods for Scheimpflug Camera

      , , ,
      Journal of Sensors
      Hindawi Limited

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          Abstract

          The Scheimpflug camera offers a wide range of applications in the field of typical close-range photogrammetry, particle image velocity, and digital image correlation due to the fact that the depth-of-view of Scheimpflug camera can be greatly extended according to the Scheimpflug condition. Yet, the conventional calibration methods are not applicable in this case because the assumptions used by classical calibration methodologies are not valid anymore for cameras undergoing Scheimpflug condition. Therefore, various methods have been investigated to solve the problem over the last few years. However, no comprehensive review exists that provides an insight into recent calibration methods of Scheimpflug cameras. This paper presents a survey of recent calibration methods of Scheimpflug cameras with perspective lens, including the general nonparametric imaging model, and analyzes in detail the advantages and drawbacks of the mainstream calibration models with respect to each other. Real data experiments including calibrations, reconstructions, and measurements are performed to assess the performance of the models. The results reveal that the accuracies of the RMM, PLVM, PCIM, and GNIM are basically equal, while the accuracy of GNIM is slightly lower compared with the other three parametric models. Moreover, the experimental results reveal that the parameters of the tangential distortion are likely coupled with the tilt angle of the sensor in Scheimpflug calibration models. The work of this paper lays the foundation of further research of Scheimpflug cameras.

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          Most cited references27

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          A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses

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            A new technique for fully autonomous and efficient 3D robotics hand/eye calibration

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              Corneal deformation measurement using Scheimpflug noncontact tonometry.

              To determine the intraexaminer repeatability and intersession reproducibility of corneal deformation measurement using Scheimpflug noncontact tonometry (Corvis ST) on normal subjects. Thirty-seven adults aged 20 to 48 years were invited to have their corneal deformation and curvature measurements taken using Corvis ST and Pentacam, respectively. Three consecutive measurements were taken for each instrument between 9:00 and 11:00 AM for intraexaminer repeatability analysis. Participants returned between 3:00 and 5:00 PM the same day for intersession reproducibility analysis. The most repeatable corneal parameter measured by Corvis ST was central corneal thickness ([CCT] ICC, 0.96; precision, 10.85 μm; repeatability, 15.34 μm; CV, 1.01%), followed by deformation amplitude ([DA] ICC, 0.80; precision, 0.08 mm; repeatability, 0.13 mm; CV, 4.33%), first applanation time ([1st A-time] ICC, 0.77; precision, 0.22 milliseconds; repeatability, 0.31 milliseconds; CV, 1.42), and intraocular pressure ([IOP] ICC, 0.75; precision, 1.39 mm Hg; repeatability, 1.97 mm Hg; CV, 4.98). Other parameters showed poor repeatability. The DA and 1st A-time showed good intersession reproducibility. The 95% limits of agreement were +0.13 to -0.13 mm for DA and +0.27 to -0.33 milliseconds for 1st A-time. The DA was negatively correlated with central corneal thickness (r = -0.53, p < 0.001) but not with corneal curvatures (flattest curvature, r = 0.13, p = 0.46; steepest curvature, r = 0.05, p = 0.75). Corneal deformation parameters DA and 1st A-time were repeatable and reproducible. A thinner cornea was associated with a higher corneal deformation. Measurement of DA serves as an indicator of corneal biomechanical properties.
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                Author and article information

                Journal
                Journal of Sensors
                Journal of Sensors
                Hindawi Limited
                1687-725X
                1687-7268
                2018
                2018
                : 2018
                :
                : 1-15
                Article
                10.1155/2018/3901431
                8e6a74b7-6c0d-432e-be71-146591f04a81
                © 2018

                http://creativecommons.org/licenses/by/4.0/

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