二维旋转平台下的相机参数标定

发布时间：2019-03-05 09:45

【摘要】：针对可旋转相机的参数标定问题,提出了一种基于二维旋转平台的相机成像模型。首先,通过一对坐标系的变换与逆变换,将相机的旋转平移变换关系转换为二维旋转平台纯旋转关系;然后,借助旋转平台读数以及相机到旋转平台的固定变换关系,实现相机内参的精确标定以及任意位置间相机外参的相互转换;最后,利用标定出的相机与旋转平台间变换矩阵实现不同位置相机参数的转换。相比于传统固定相机的标定方法,本文提出的方法标定获得的相机内参具有更好的收敛性,而且能够标定出相机到旋转平台的变换矩阵,从而实现相机坐标系变换参数的精确计算。实验结果表明,在标定模板图像数量相同时,与常用的张氏标定法相比,本文提出的方法标定获得的相机内参具有更快的收敛速度。棋盘格角点重投影坐标与实际拍摄图像中棋盘格角点坐标相对比,平均误差约为0.12pixel,表明该方法具有较高精度。
[Abstract]:A camera imaging model based on a two-dimensional rotating platform is proposed to calibrate the parameters of a rotatable camera. Firstly, through the transformation and inverse transformation of a pair of coordinate systems, the rotation translation transformation relation of the camera is transformed into the pure rotation relation of the two-dimensional rotating platform. Then, with the help of the reading of the rotating platform and the fixed transformation relationship from the camera to the rotating platform, the accurate calibration of the internal parameters of the camera and the conversion of the external and external parameters of the camera at any position are realized. Finally, the transformation matrix between camera and rotating platform is used to realize the conversion of camera parameters at different positions. Compared with the traditional calibration method of fixed camera, the method proposed in this paper has better convergence and can calibrate the transformation matrix from camera to rotating platform. As a result, the accurate calculation of camera coordinate transformation parameters is realized. The experimental results show that, when the number of calibration template images is the same, compared with the usual Zhang calibration method, the internal parameters of camera calibrated by the proposed method have a faster convergence speed. The average error of the double projection coordinates of checkerboard corner points is about 0.12 pixels, which indicates that the method has high accuracy compared with that of the actual shot images of chessboard corner points.
【作者单位】：南京理工大学电子工程与光电技术学院;
【基金】：国家自然科学基金面上项目(No.61675099);国家自然科学基金资助项目(No.61271332) 江苏省基础研究计划青年基金资助项目(No.BK20130769)
【分类号】：TP391.41

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