摘要
本文在分析完整的摄像机镜头畸变模型的基础上,提出了一种新的标定算法。该算法包括三个步骤,首先在不考虑镜头畸变的情况下利用标定块上的中间若干个点,采用线性优化方法求出除畸变系数以外的其他外部参数和主要的内部参数;然后固定上述已求得的参数,利用线性优化方法求解畸变系数;最后对所有内部参数和外部参数进行全局非线性优化。最后对本文的标定算法进行了标定实验,实验结果表明,本文算法的标定精度可以达到0.0367mm,可以满足高精度三维测量及其他应用的要求。
On the basis of analyzing complete camera distortion model, a new calibration algorithm is proposed, The new algorithm consists of three steps, In the first step, the calibration parameters are estimated using a close-form solution based on a distortion-free camera model, In the second step, estimating the set of distortion parameters with the other parameters fixed. In the third step, the parameters estimated in the first step are improved iteratively through a nonlinear optimization, and makes all the parameters globalization. Very good results are obtained with real data calibration. The results show the precision of the new proposed method is up to 0.0367 mm, which meets the requirements of high precision 3D measurement and other application.
出处
《光电工程》
EI
CAS
CSCD
北大核心
2008年第4期58-63,共6页
Opto-Electronic Engineering
基金
湖北省自然科学基金创新群体项目--快速制造关键技术(2004ABC001)
关键词
计算机视觉
摄像机标定
非线性优化
computer vision
camera calibration
nonlinear optimization
