The Comparison of Camera Calibration Methods Based on Structured-Light Measurement

Camera calibration is a necessary step in using 3D computer vision to extract metric information from 2D images.  Based on the positioning theory of the linear-structured-light, this paper analyses and compares the three popular calibration methods: typical linear calibration, Tsai’s two-stage calibration and Zhang’s planar pattern calibration in the aspects of referenced objects, arithmetic and precision by measuring the position of space points. Considering the feature points’ importance, we adopted an improved arithmetic based on Harris to extract the points of the planar pattern. It is concluded that Zhang’s method has the best practicability and validity, and this has been verified by experiment.

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