极线几何
重射误差
校准
稳健性(进化)
人工智能
计算机科学
计算机视觉
观测误差
失真(音乐)
泽尼克多项式
算法
摄像机切除
数学
光学
物理
图像(数学)
放大器
化学
带宽(计算)
波前
统计
基因
生物化学
计算机网络
作者
Xia Liu,Zhenyu Liu,Guifang Duan,Jin Cheng,Xuetao Jiang,Jianrong Tan
出处
期刊:Applied Optics
[The Optical Society]
日期:2018-06-15
卷期号:57 (18): 5130-5130
被引量:32
摘要
Precise calibration of a binocular vision system is the foundation of binocular vision measurement. In this paper, we propose a highly precise and robust binocular camera calibration method, which is devoted to minimize the error between the geometric relation of 3D reconstructed feature points and the ground truth, such as adjacent distance error, collinear error, and right-angle error. In addition, the reprojection error and epipolar are introduced to satisfy the homography relation and epipolar geometry theory better. We optimize all intrinsic parameters, extrinsic parameters, and distortion parameters to minimize the objective function, which is the sum of a series of nonlinear least squares terms. Levenberg-Marquardt iterative algorithm is used to find the optimal solution of the camera parameters. To test the precision and robustness of the proposed method, both actual measurement experiments and Gauss noise-adding experiments are carried out. The experimental results show that compared with the other two calibration methods in the contrast experiment, the distance measurement error, collinear error, and right-angle error are reduced dramatically. It is noticeable that in Gauss noise-adding experiments, the calibration parameters estimated by the proposed method are more stable.
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