一种双正交消隐点的双目相机标定方法

赵亚凤; 胡峻峰

doi:10.3788/YJYXS20163110.0958

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一种双正交消隐点的双目相机标定方法

显示与图像 | 更新时间：2020-07-07

- 一种双正交消隐点的双目相机标定方法
- Binocular self calibration using two pairs of orthogonal vanishing points
- 液晶与显示 2016年31卷第10期页码：958-966
- 作者机构：
  
  东北林业大学机电工程学院, 黑龙江哈尔滨 150040
- 作者简介：
  
  [ "赵亚凤(1980-), 女, 湖北公安人, 博士, 讲师, 分别于2006年于哈尔滨工程大学获得硕士学位, 2016年获得东北林业大学博士学位, 主要研究方向为机器视觉及模式识别。E-mail:nefuzyf@126.com" ]
  胡峻峰(1980-), 男, 黑龙江哈尔滨人, 博士, 讲师, 分别于2008, 2015年获得东北林业大学硕士、博士学位。主要研究方向为图像处理、智能控制和机器视觉。E-mail:heaven_pro@163.com
- 基金信息：
  
  中央高校基本科研业务费资助项目(2572015BB11);黑龙江省青年基金(QC2015080);Fundamental Research Funds For the Central Universities of China(257215BB11);Heilongjiang Province Science Foundation for Youth(QC2015080)
- DOI：10.3788/YJYXS20163110.0958
  中图分类号： TP394.1;TH691.9
- 收稿日期：2016-06-12，
  
  录用日期：2016-7-18，
  
  纸质出版日期：2016-10
- 稿件说明：
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赵亚凤, 胡峻峰. 一种双正交消隐点的双目相机标定方法[J]. 液晶与显示, 2016,31(10):958-966.

Ya-feng ZHAO, Jun-feng HU. Binocular self calibration using two pairs of orthogonal vanishing points[J]. Chinese journal of liquid crystals and displays, 2016, 31(10): 958-966.
赵亚凤, 胡峻峰. 一种双正交消隐点的双目相机标定方法[J]. 液晶与显示, 2016,31(10):958-966. DOI： 10.3788/YJYXS20163110.0958.

Ya-feng ZHAO, Jun-feng HU. Binocular self calibration using two pairs of orthogonal vanishing points[J]. Chinese journal of liquid crystals and displays, 2016, 31(10): 958-966. DOI： 10.3788/YJYXS20163110.0958.

摘要

为了保证双目相机标定精度的同时，提高算法速度。利用田字形模板中的两对正交消隐点，拍摄两幅图像，实现快速标定。首先，提出了消隐点寻优的方法来提取每幅图像中误差最小的两对正交消隐点，线性计算相机主点和归一化焦距，作为内参数的初值。再根据同一幅图像消隐点共线和所有直线畸变后也为直线的原则，构建约束函数，利用优化的差分进化算法进行全局寻优，完成相机畸变校正。最后，根据优化后消隐点坐标求得左右相机的旋转矩阵，并结合左右相机的角点世界坐标，利用刚性变换求得平移向量。双目标定的平均重构误差为0.598 pixel，跟传统方法标定误差相当。该标定算法重构误差与传统算法在一个级别，能满足标定中稳定可靠、精度高、抗干扰能力强等要求。

Abstract

In order to realize fast and accurate binocular calibration

two pairs of orthogonal vanishing points product from square template were used. This method requires only two images. Firstly

two pairs of orthogonal vanishing point were extracted from each image; secondly

winner point and focal length on each single camera were solved by linear algorithm; thirdly

considering the radial lens distortion

distortion correction was implemented by linear constraints. During this process

the optimization differential evolution algorithm was proposed. Parameters within the solution were set as initial value. Line collinear features were set as constrained optimization parameters. According to the coordinates of 4 vanishing point

by using the infinite homography matrix rotation orthogonal constraint

the initial values of the rotation matrix can be obtained and more accurately calculated rotation matrix can be obtained by the iterative method. Experimental results indicate that the reconstruction error is 0.598 pixel. The experimental results show that the calibration method can meet the precision requirements

and it is stable and reliable

high precision and strong robustness for self calibration.

关键词

Keywords

references

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