激光与光电子学进展, 2020, 57 (10): 101505, 网络出版: 2020-05-08   

基于全站仪的大型三维形貌摄影测量方法 下载: 1132次

Three-Dimensional Measurement of Large-Scale Objects Using Photogrammetry Based on Total Station
作者单位
1 沈阳建筑大学机械工程学院, 辽宁 沈阳 110168
2 西安交通大学机械制造系统工程国家重点实验室, 陕西 西安 710049
摘要
以摄影测量为基础,旨在采用全站仪与普通数码相机相结合的方式,实现大型物体三维形状和颜色信息的高精度、快速、灵活获取。将普通数码相机刚性连接到全站仪的望远镜上搭建组合测量系统,借助全站仪的角度读数随时记录相机位姿;为了减弱窄视场相机标定中的参数耦合,先根据相机的物理特性直接标定相机主距参数;通过建立控制场确定其余相机的内参数及望远镜相对相机的位姿参数;借助两个公共标志点实现测站的任意转换,进而实现大型物体的三维形貌测量。实验表明,所提方法的长度测量相对误差不超过±1/100,角度误差不超过±0.6°,目前能够实现中等精度的大型物体三维形貌测量。
Abstract
Based on photogrammetry, this study aims to determine a highly accurate, efficient, and flexible approach for obtaining three-dimensional shape and color information of large-scale objects using a total station and a common digital camera. An ordinary digital camera was rigidly connected to the telescope of a total station to build a combined measurement system, and the camera's posture was recorded at all times using the angle reading of the total station. To weaken the parameter coupling while calibrating a camera with a narrow field of view, the principal distance parameter was first directly calibrated based on the physical characteristics of the camera. The other intrinsic parameters of the camera and pose parameters of the telescope associated with the camera were determined by establishing a control field. The station was freely transformed using two common points to achieve the three-dimensional measurement of large-scale objects. Experiments show that the relative error of the length achieved using this method does not exceed ±1/100, and the angle error does not exceed ±0.6°, implying that this method can currently realize three-dimensional measurement of large-scale objects with medium accuracy.

杨谢柳, 尹晨宇, 方素平, 刘士明. 基于全站仪的大型三维形貌摄影测量方法[J]. 激光与光电子学进展, 2020, 57(10): 101505. Xieliu Yang, Chenyu Yin, Suping Fang, Shiming Liu. Three-Dimensional Measurement of Large-Scale Objects Using Photogrammetry Based on Total Station[J]. Laser & Optoelectronics Progress, 2020, 57(10): 101505.

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