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Camera Rapid Calibration Method for Mobile Road Measurement System

机译：相机移动路测量系统的快速校准方法

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摘要

In recent years, a variety of mobile road measurement equipment has emerged and become an important means of collecting spatial information. As an important part of the mobile road measurement system, a camera's function implementation and data accuracy largely depend on its internal parameters and the rotation and translation parameters corresponding to the world coordinate system. Based on this and on the traditional camera calibration method, radial and tangential distortion for monocular camera calibration is introduced in this article to establish a calibration model, and the nonlinear least-squares Levenberg-Marquardt optimization algorithm is used in iterative calculation. The parameters provide a solution to the problem of rapid calibration of camera modules in mobile road measurement systems. The camera parameters obtained by the calibration algorithm in this study are used for visual reconstruction. Compared with two Zhang Zhengyou calibration methods optimized by the Gauss-Newton method, the former has an average pixel offset of 0.28 pixel and the latter has deviations of 0.66 and 0.38 pixel. Using a monocular camera to collect data on geometric targets on a road, the average relative error does not exceed 2.16%. Experiments show that this method can obtain calibration results quickly and accurately. (C) 2020 Society for Imaging Science and Technology.
机译：近年来，出现了各种移动道路测量设备，成为收集空间信息的重要手段。作为移动道路测量系统的重要组成部分，相机的功能实现和数据准确性主要取决于其内部参数和与世界坐标系对应的旋转和翻译参数。基于这一和传统的相机校准方法，在本文中介绍了用于单眼相机校准的径向和切向失真，以建立校准模型，并且非线性最小二乘levenberg-Marquardt优化算法用于迭代计算。该参数提供了移动道路测量系统中相机模块快速校准问题的解决方案。本研究中校准算法获得的相机参数用于视觉重建。与张正友校准方法相比，通过高斯 - 牛顿方法优化，前者的平均像素偏移为0.28像素，后者具有0.66和0.38像素的偏差。使用单眼摄像机收集在道路上的几何目标上的数据，平均相对误差不超过2.16％。实验表明，该方法可以快速准确地获得校准结果。 （c）2020年影像科技协会。

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  • 来源
    《Journal of Imaging Science and Technology》 |2020年第4期|040406.1-040406.11|共11页
  • 作者

    Huang He; Xue Yizhou; Luo Dean;

  • 作者单位

    Beijing Univ Civil Engn & Architecture Sch Geomat & Urban Spatial Informat Beijing 102616 Peoples R China;

    Beijing Univ Civil Engn & Architecture Sch Geomat & Urban Spatial Informat Beijing 102616 Peoples R China;

    Beijing Univ Civil Engn & Architecture Sch Geomat & Urban Spatial Informat Beijing 102616 Peoples R China;

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