双目立体视觉测量系统的标定

杨景豪; 刘巍; 刘阳; 王福吉; 贾振元

doi:doi:10.3788/ope.20162402.0300

光学精密工程, 2016, 24 (2): 300, 网络出版: 2016-03-28

双目立体视觉测量系统的标定

Calibration of binocular vision measurement system

论文大纲

杨景豪 ^*刘巍刘阳王福吉贾振元

作者单位

大连理工大学教育部精密特种加工实验室, 辽宁大连 116024

视觉测量大视场立体视觉双目视觉测量系统摄像机标定 vision measurement large field of view stereo vision binocular vision measurement system camera calibration

摘要

考虑传统的自标定方法虽然无需场景信息即可实现摄像机标定, 但是标定精度较低, 故本文提出了一种新的大视场双目视觉测量系统自标定方法。该方法无需高精度标定板或者标定物, 仅需利用空间中常见的平行线和垂直线建立摄像机参数与特征线间的约束方程, 即可实现摄像机的内参数与旋转矩阵标定; 同时利用空间中距离已知的3个空间点即可线性标定两摄像机间的平移向量。通过标定实验对本文提出的方法进行了验证。结果表明: 该方法标定精度能够达到0.51%, 可以较高精度地标定双目测量系统。由于避免了大视场测量系统标定中大型标定物制造困难, 以及摄像机自标定过程中算法冗杂, 标定精度不高等问题, 该方法操作简便, 精度较好, 适用于大视场双目测量系统的在线标定。

Abstract

When traditional self-calibration methods are used to calibrate the cameras without scene information, it usually shows lower calibration accuracy. In order to solve this problem, an improved self-calibration method for a binocular vision measurement system was proposed. Without high-accuracy calibration pattern, the proposed method could calibrate intrinsic parameters and rotation matrixes only by using parallel and perpendicular lines to establishing the constraint equation between the camera parameter and the characteristic line. Meanwhile, the translation vector was calibrated by feature points with the known distances between them. The calibration experiment was conducted to verify the proposed method. It shows that the proposed method calibrates the binocular vision measurement system in high accuracy, the accuracy reaches to 0.51%. As the proposed method avoids the difficulties from the high-accuracy calibration pattern needed in the calibration of measuring system, and the complex algorithm and low calibration accuracy in camera self-calibration, it has advantages of easy operating and high accuracy.

参考文献

[1] 解则晓, 韩振华, 高翔. 光笔式单目视觉测量系统的关键技术［J］.中国光学, 2013, 6(5): 780-787.

XIE Z X, HAN ZH H, GAO X. Key technologies of monocular vision measurement system with light pen ［J］. Chinese Optics, 2013, 6(5): 780-787. (in Chinese)

[2] JIA Z, WANG B, LIU W, et al.. An improved image acquiring method for machine vision measurement of hot formed parts［J］. Journal of Materials Processing Technology, 2010, 210(2): 267-271.

[3] 刘建伟, 梁晋, 梁新合, 等. 大尺寸工业视觉测量系统［J］. 光学精密工程, 2010, 18(1): 126-134.

LIU J W, LIANG J, LIANG X H, et al.. Industrial vision measuring system for large dimension work-pieces ［J］. Opt. Precision Eng., 2010, 18(1): 126-134. (in Chinese)

[4] 孙军华, 张广军, 魏振忠, 等. 大型自由曲面移动式三维视觉测量系统［J］. 仪器仪表学报, 2007, 27(12): 1688-1691.

SUN J H, ZHANG G J, WEI ZH ZH. Mobile 3D vision measurement system for large-scale free form surface［J］. Chinese Journal of Scientific Instrument, 2007, 27(12): 1688-1691. (in Chinese)

[5] 马颂德, 张正友. 计算机视觉: 计算理论与算法基础［M］. 北京: 科学出版社, 1998.

MA S D, ZHANG ZH Y. The Computer Vision——Computation Theory and Fundamental Algorithm ［M］. Beijing : The Science Press , 1998. (in Chinese)

[6] 张广军. 视觉测量［M］. 北京: 科学出版社, 2008.

ZHANG G J. Vision Measurement ［M］. Beijing: Science Press, 2008. (in Chinese)

[7] ZHANG Z. Flexible camera calibration by viewing a plane from unknown orientations［C］. The Proceedings of the Seventh IEEE International Conference on Computer Vision, IEEE, 1999, 1: 666-673.

[8] HEIKKILA J, SILVN O. A four-step camera calibration procedure with implicit image correction［C］. 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 1997: 1106-1112.

[9] 刘书桂, 姜珍珠, 董英华, 等. 采用移动光靶标的分区域相机标定［J］. 光学精密工程, 2014, 22(2): 259-265.

LIU SH G, JIANG ZH ZH, DONG Y H, et al.. Sub-regional camera calibration based on moving light target ［J］. Opt. Precision Eng., 2014, 22(2): 259-265. (in Chinese)

[10] 徐巧玉, 叶东, 车仁生. 基于光学参考棒的立体视觉测量系统现场标定技术［J］. 光学学报, 2008, 28(1): 81-86.

XU Q Y, YE D, CHE R SH. On-line calibration of stereo vision measurement system based on optical reference bar［J］. Acta Optica Sinica, 2008, 28(1): 81-86. (in Chinese)

[11] 黄风山, 刘恩福, 方忆湘, 等. 基于智能三坐标测量机的零件位姿单目立体视觉识别［J］. 光学精密工程, 2013, 21(5): 1326-1332.

HUANG F SH, LIU E F, FANG Y X, et al.. Single camera stereo vision recognization for Parts’ pose based on intelligent three coordinate measuring machine［J］. Opt. Precision Eng., 2013, 21(5): 1326-1332. (in Chinese)

[12] 王向军, 王晶, 刘峰, 等. 野外大视场双目视觉物体定位监测系统的单参数快速标定［J］. 光学精密工程, 2013, 21(10): 2664-2670.

WANG X J, WANG J, LIU F, et al.. Fast calibration for binocular vision measuring system with a large field ［J］. Opt. Precision Eng., 2013, 21(10): 2664-2670. (in Chinese)

[13] 周富强, 邾继贵, 杨学友, 等. CCD 摄像机快速标定技术［J］. 光学精密工程, 2000, 8(1): 96-100.

ZHOU F Q, ZHU J G, YANG X Y, et al.. A high speed CCD camera calibration technique ［J］. Opt. Precision Eng., 2000, 8(1): 96-100. (in Chinese)

[14] FAIG W. Calibration of close-range photogrammetric systems: Mathematical formulation［J］. Photogrammetric Engineering and Remote Sensing,1975, 41(12): 1479-1486.

[15] TSAI R Y. An efficient and accurate camera calibration technique for 3D machine vision［C］. Proceeding IEEE Conference on Computer Vision and Pattern Recognition, IEEE, 1986: 364-374.

[16] TSAI R Y. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses［J］. IEEE Journal of Robotics and Automation, 1987, 3(4): 323-344.

[17] ABEL-AZIZ Y I, KARARA H M. Direct linear transformation from comparator coordinates into object space coordinates［J］. Urbana, IL: American Society of Photogrammetry, 1971: 1-18.

[18] ZHANG Z. A flexible new technique for camera calibration［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(11): 1330-1334.

[19] HARTLEY R I. Self-calibration of stationary cameras［J］. International Journal of Computer Vision, 1997, 22(1): 5-23.

[20] MA S D. A self-calibration technique for active vision systems［J］. IEEE Transactions on Robotics and Automation, 1996, 12(1): 114-120.

[21] 雷成, 吴福朝. 一种新的基于主动视觉系统的摄像机自标定方法［J］. 计算机学报, 2000, 23(11): 1130-1139.

LEI CH, WU F CH. A new camera self-calibration method based on active vision system［J］. Chinese Journal of Computers, 2000, 23(11): 1130-1139. (in Chinese)

[22] MERRAS M, EL AKKAD N, SAAIDI A, et al.. Camera self calibration with varying parameters by an unknown three dimensional scene using the improved genetic algorithm［J］. 3D Research, 2015, 6(1): 1-14.

[23] ZHAO Y, XU L. Self-calibration of monocular vision system based on planar points［C］. International Society for Optics and Photonics, IS&T/SPIE Electronic Imaging, 2015: 94050H-94050H-9.

[24] FAUGERAS O D, LUONG Q T, MAYBANK S J. Camera self-calibration: Theory and experiments［C］. Computer Vision—ECCV'92, Springer Berlin Heidelberg, 1992: 321-334.

[25] HARTLEY R. In defense of the eight-point algorithm［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(6): 580-593.

[26] 霍炬, 杨卫, 杨明. 基于消隐点几何特性的摄像机自标定方法［J］. 光学学报, 2010,30(2): 465-472.

HUO J, YANG W, YANG M. A self-calibration technique based on the geometry property of the vanish point［J］. Acta Optica Sinica, 2010, 30(2): 465-472. (in Chinese)

[27] 吴福朝. 计算机视觉中的数学方法［M］. 北京: 科学出版社, 2008.

WU F CH. Mathematical Methods in Computer Vision［M］. Beijing: Science Press, 2008.(in Chinese)

杨景豪, 刘巍, 刘阳, 王福吉, 贾振元. 双目立体视觉测量系统的标定[J]. 光学精密工程, 2016, 24(2): 300. YANG Jing-hao, LIU Wei, LIU Yang, WANG Fu-ji, JIA Zhen-yuan. Calibration of binocular vision measurement system[J]. Optics and Precision Engineering, 2016, 24(2): 300.

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