Acquisition of camera dynamic extrinsic parameters in free binocular stereo vision system

doi:10.11772/j.issn.1001-9081.2017.10.2888

Journal of Computer Applications ›› 2017, Vol. 37 ›› Issue (10): 2888-2894.DOI: 10.11772/j.issn.1001-9081.2017.10.2888

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Acquisition of camera dynamic extrinsic parameters in free binocular stereo vision system

LI Xiao^1,2, GE Baozhen^1,2, LUO Qijun^1,2,3, LI Yunpeng^1,2, TIAN Qingguo^1,2

1. School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China;
2. Key Laboratory of Opto-Electronics Information Technology of Ministry of Education, Tianjin 300072, China;
3. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China

Received:2017-04-07 Revised:2017-06-03 Online:2017-10-10 Published:2017-10-16
Supported by:
This work is partially supported by the National Natural Science Foundation of China (61535008).

自由双目立体视觉摄像机动态外参数的获取

李肖^1,2, 葛宝臻^1,2, 罗其俊^1,2,3, 李云鹏^1,2, 田庆国^1,2

1. 天津大学精密仪器与光电子工程学院, 天津 300072;
2. 光电信息技术教育部重点实验室, 天津 300072;
3. 中国民航大学电子信息与自动化学院, 天津, 300300

通讯作者: 葛宝臻(1964-),男,内蒙古卓资人,教授,博士,主要研究方向:激光三维彩色数字成像、光电检测、激光粒子测量,E-mail:gebz@tju.edu.cn
作者简介:李肖(1990-),女,河北石家庄人,硕士研究生,主要研究方向:双目立体视觉;葛宝臻(1964-),男,内蒙古卓资人,教授,博士,主要研究方向:激光三维彩色数字成像、光电检测、激光粒子测量;罗其俊(1982-),男,湖北云梦人,讲师,博士研究生,主要研究方向:计算机视觉、智能系统;李云鹏(1987-),男,天津人,博士研究生,主要研究方向:激光三维彩色数字成像;田庆国(1973-),男,河北唐山人,讲师,博士,主要研究方向:计算机可视化、图像图形学.
基金资助:
国家自然科学基金资助项目（61535008）。

Abstract

Abstract: Aiming to solve the change of the extrinsic parameters between the two cameras in free binocular stereo vision system caused by the rotation of the cameras, a method for acquiring the dynamic extrinsic parameters based on calibration of rotation axis was proposed. Multiple rotation and translation matrixes were obtained by the calibration at different positions, then the parameters of rotation axis could be calculated by using least square method. Combined with the intrinsic and extrinsic parameters at initial position and rotation angle, the dynamic extrinsic parameters between the two cameras could be calculated in real time. The chessboard corners were reconstructed with the dynamic extrinsic parameters calculated by the proposed method, the result showed that the average error was 0.241mm and the standard deviation was 0.156mm. Compared with the calibration method based on multiple-plane calibration target, the proposed method is easier to implement and has higher precision, where dynamic extrinsic parameters can be acquired without real-time calibration.

Key words: machine vision, free binocular stereo vision, dynamic extrinsic parameter, calibration of rotation axis, 3D reconstruction

摘要： 针对自由双目立体视觉中由于摄像机旋转导致的摄像机外参数变化的问题，提出一种基于旋转轴标定的动态外参数获取方法。在多个不同位置，立体标定得到多组旋转平移矩阵，利用最小二乘法求解旋转轴参数；结合初始位置左右摄像机的内、外参数及旋转角度，实时获取左右摄像机的外参数。利用所提方法获取动态外参数，并对棋盘角点进行三维重建，平均误差为0.241mm，标准差为0.156mm；与基于多平面标靶的标定方法相比，精度高且操作简单。所提方法无需实时标定，可完成摄像机旋转情况下动态外参数的获取。

关键词: 机器视觉, 自由双目立体视觉, 动态外参数, 旋转轴标定, 三维重建

CLC Number:

TP391.41

LI Xiao, GE Baozhen, LUO Qijun, LI Yunpeng, TIAN Qingguo. Acquisition of camera dynamic extrinsic parameters in free binocular stereo vision system[J]. Journal of Computer Applications, 2017, 37(10): 2888-2894.

李肖, 葛宝臻, 罗其俊, 李云鹏, 田庆国. 自由双目立体视觉摄像机动态外参数的获取[J]. 计算机应用, 2017, 37(10): 2888-2894.

References

[1] JENKIN M R M, JEPSON A D. The measurement of binocular disparity[M]//CANTONI V, GESÙ V D, LEVIALDI S. Image Analysis and Processing Ⅱ. Berlin: Springer, 1988: 237-244.
[2] 张旭苹, 汪家其, 张益昕, 等. 大尺度三维几何尺寸立体视觉测量系统实现[J]. 光学学报, 2012, 32(3): 0315002. (ZHANG X P, WANG J Q, ZHANG Y X, et al. Large-scale three-dimensional stereo vision geometric measurement system[J]. Acta Optical Sinica, 2012, 32(3): 0315002.)
[3] 马琳, 郑南宁, 李青, 等. 自主车辆视觉系统的摄像机动态自标定算法[J]. 西安交通大学学报, 2005, 39(10): 1072-1076. (MA L, ZHENG N N, LI Q, et al. Dynamic approach of camera auto-calibration for vision system on autonomous vehicle[J]. Journal of Xi'an Jiaotong University, 2005, 39(10): 1072-1076.)
[4] WANG L L, TSAI W H. Camera calibration by vanishing lines for 3-D computer vision[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991: 370-376.
[5] LIU Y, WU Y, WU M, et al. Planar vanishing points based camera calibration[C]//ICIG 2004: Proceedings of the Third International Conference on Image and Graphics. Piscataway, NJ: IEEE, 2004: 460-463.
[6] 王涛, 谢少荣, 潘智昊, 等. 基于双目立体视觉的摄像机外参数快速在线自标定算法[J]. 机械工程师, 2009(1): 104-106. (WANG T, XIE S R, PAN Z H, et al. A quick and on-line self-calibration algorithm for external camera parameters based on binocular vision[J]. Mechanical Engineer, 2009(1): 104-106.)
[7] DANG T, HOFFMANN C, STILLER C. Self-calibration for active automotive stereo vision[C]//Proceedings of the 2006 IEEE Intelligent Vehicles Symposium. Piscataway, NJ: IEEE, 2006: 364-369.
[8] 尚倩, 阮秋琦, 李小利. 双目立体视觉的目标识别与定位[J]. 智能系统学报, 2011, 6(4): 303-311. (SHANG Q, RUAN Q Q, LI X L. Target recognition and location based on binocular stereo vision[J]. CAAI Transactions on Intelligent Systems, 2011, 6(4): 303-311.)
[9] 曾慧, 高伟, 胡占义. 四自由度双目视觉系统中的摄像机标定方法: CN103854291A [P]. 2014-06-11. (ZENG H, GAO W, HU Z Y. The calibration of camera in four-freedom binocular vision system: CN103854291A [P]. 2014-06-11.)
[10] 祝琨, 杨唐文, 阮秋琦, 等. 基于双目视觉的运动物体实时跟踪与测距[J]. 机器人, 2009, 31(4): 327-334. (ZHU K, YANG T W, RUAN Q Q, et al. Real-time tracking and measuring of moving objects based on binocular vision[J]. Robot, 2009, 31(4): 327-334.)
[11] 孔令富, 景荣, 赵立强. 圆轨双链主动视觉机构标定系统的设计[J]. 计算机工程与设计, 2010, 31(8): 1882-1885. (KONG L F, JING R, ZHAO L Q. Design of calibration system of double-stranded active vision on circular orbit[J]. Computer Engineering and Design, 2010, 31(8): 1882-1885.)
[12] NIU Z, LIU K, WANG Y, et al. Calibration method for the relative orientation between the rotation axis and a camera using constrained global optimization[J]. Measurement Science and Technology, 2017, 28(5):055001.
[13] LI X, JIN J, LI W. Stereovision measurement technology with rotation CCD camera of multi-object[J]. Proceedings of the SPIE, 2011, 8205(4): 14.
[14] TSAI R Y, LENZ R K. A new technique for fully autonomous and efficient 3D robotics hand/eye calibration[J]. IEEE Transactions on Robotics & Automation, 1989, 5(3): 345-358.
[15] DANⅡLIDIS K. Hand-eye calibration using dual quaternions[J]. International Journal of Robotics Research, 1998, 18(3): 286-298.
[16] 赖小波. 机器人双目立体视觉若干关键理论问题及其技术实现研究[D]. 杭州: 浙江大学, 2010. (LAI X B. Research on some key theoretical issues for robotic binocular stereo vision and its techniques implementation[D]. Hangzhou: Zhejiang University, 2010.)
[17] 王鹏, 孙长库. 双目视觉转轴标定方法: CN101216296 [P]. 2008-07-09. (WANG P, SUN C K. Calibration of rotation axis based on binocular vision: CN101216296 [P]. 2008-07-09.)
[18] 和青芳. 计算机图形学原理及算法教程[M]. 北京: 清华大学出版社, 2010: 94-96. (HE Q F. Principles of computer graphics and algorithms[M]. Beijing: Tsinghua University Press, 2010: 94-96.)
[19] BRADSKI G, KAEBLER A. Learning OpenCV[M]. Sebastopol: O'Reilly Media, 2008: 401-403, 427-430.
[20] PARK S-Y, SUBBARAO M. A multiview 3D modeling system based on stereo vision techniques[J]. Machine Vision and Application, 2005, 16(3): 148-156.
[21] SADLO F, WEYRICH T, PEIKERT R, et al. A practical structured light acquisition system for point-based geometry and texture[C]//SPBG 2005: Proceedings of the Second Eurographics, IEEE VGTC Conference on Point-Based Graphics. Piscataway, NJ: IEEE, 2005: 1-10.
[22] 李怀泽, 沈会良, 程岳. 基于旋转多视角深度配准的三维重建方法[J]. 计算机应用, 2012, 32(12): 3365-3368. (LI H Z, SHEN H L, CHENG Y. 3D reconstruction method based on turntable multiple-view registration[J]. Journal of Computer Applications, 2012, 32(12): 3365-3368.)
[23] 徐永安, 杨钦, 怀进鹏. 激光旋转扫描测量系统中转轴标定及多视拼合[J]. 中国激光, 2005, 32(5): 659-662. (XU Y A, YANG Q, HUAI J P. Calibration of the axis of the turntable in 4-axis laser measuring system and registration of multi-view[J]. Chinese Journal of Lasers, 2005, 32(5): 659-662.)
[24] 胡民政, 习俊通. 面向结构光三维测量的两轴转台标定[J]. 上海交通大学学报, 2010, 44(4): 506-511. (HU M Z, XI J T. Two-axis turntable calibration in three-dimensional structured light measurement system[J]. Journal of Shanghai Jiaotong University, 2010, 44(4): 506-511.)
[25] ZHANG Z Y. A flexible new technique for camera calibration[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(11): 1330-1334.
[26] 郭涛, 达飞鹏, 方旭. 小视场环境下的摄像机标定[J]. 中国激光, 2012, 39(8): 0808001. (GUO T, DA F P, FANG X. Camera calibration under small field of view[J]. Chinese Journal of Lasers, 2012, 39(8): 0808001.)
[27] 郑圣子, 李湘旭, 孙志超. 新型移动机器人激光测距雷达的研究[J]. 计算机测量与控制, 2011, 19(5): 1094-1097. (ZHENG S Z, LI X X, SUN Z C. Novel design of low cost moblie robot laser scanner[J]. Computer Measurement & Control, 2011, 19(5): 1094-1097.)

Acquisition of camera dynamic extrinsic parameters in free binocular stereo vision system

自由双目立体视觉摄像机动态外参数的获取

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