2021
DOI: 10.1088/1361-6501/abe447
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An improved projector calibration method for structured-light 3D measurement systems

Abstract: In a structured-light three-dimensional measurement system, understanding the optical configuration of the projector and suppressing the eccentricity error caused by the camera perspective projection are critical to realize high-precision measurement. In this paper, we analyze the special offset optical structure in commercial projectors, where a larger diameter lens is used to ensure the quality of the projected image, and the position of the principal point has been shifted. Meanwhile, a projector calibratio… Show more

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Cited by 10 publications
(2 citation statements)
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“…Although commercial projectors generally have gamma nonlinear preset values to better adapt to human visual perception, projector nonlinear errors can be well handled through calibration or post-processing compensation methods [23]. Distortions of camera and projector lenses can also be corrected and compensated through calibration [35,36]. In contrast, intensity noise and motion artifacts are random errors that cannot be easily controlled.…”
Section: Introductionmentioning
confidence: 99%
“…Although commercial projectors generally have gamma nonlinear preset values to better adapt to human visual perception, projector nonlinear errors can be well handled through calibration or post-processing compensation methods [23]. Distortions of camera and projector lenses can also be corrected and compensated through calibration [35,36]. In contrast, intensity noise and motion artifacts are random errors that cannot be easily controlled.…”
Section: Introductionmentioning
confidence: 99%
“…In another aspect, due to the error caused by various factors, BA algorithm is often introduced in vision calibration to reduce the re-projection error and optimize the calibration parameters. The use of BA algorithm can achieve the jointly optimal estimate of the system parameters and 3D world coordinates of the feature points by minimizing the model of the error function [ 15 , 16 ].…”
Section: Introductionmentioning
confidence: 99%