Zhao H Z, Gao N, Meng Z Z, et al. Method of simultaneous calibration of dual view 3D measurement system[J]. Opto-Electron Eng, 2021, 48(3): 200127. doi: 10.12086/oee.2021.200127
Citation: Zhao H Z, Gao N, Meng Z Z, et al. Method of simultaneous calibration of dual view 3D measurement system[J]. Opto-Electron Eng, 2021, 48(3): 200127. doi: 10.12086/oee.2021.200127

Method of simultaneous calibration of dual view 3D measurement system

    Fund Project: Major Project of the Scientific Equipment Development of China (2017YFF0106404), National Natural Science Foundation of China (51675160), and Major Basic Research Projects of Hebei Applied Basic Research Program (15961701D)
More Information
  • In view of the limitations of the existing methods when the camera has no common field of view, this paper proposes a method of using two plane calibration plates to calibrate two cameras at the same time. By deriving the coordinate transformation between the two cameras and two calibration plates, the solution of the relative pose relationship between any camera and the reference camera is transformed into a more mature hand-eye calibration equation. The experimental results show that this method can achieve simultaneous calibration of two cameras, and the absolute error is less than 0.089 mm. In the dual vision 3D measurement system, the cumulative error with phase height is less than 0.116 mm, which can provide a reliable initial value for the next step of data fusion.
  • 加载中
  • [1] 白雪飞, 张宗华. 基于彩色条纹投影术的三维形貌测量[J]. 仪器仪表学报, 2017, 38(8): 1912-1925. doi: 10.3969/j.issn.0254-3087.2017.08.009

    CrossRef Google Scholar

    Bai X F, Zhang Z H. 3D shape measurement based on colour fringe projection techniques[J]. Chin J Sci Instrum, 2017, 38(8): 1912-1925. doi: 10.3969/j.issn.0254-3087.2017.08.009

    CrossRef Google Scholar

    [2] 唐燕, 陈文静, 张强, 等. 神经网络获取三维面形研究[J]. 光电工程, 2007, 34(12): 61-65. doi: 10.3969/j.issn.1003-501X.2007.12.013

    CrossRef Google Scholar

    Tang Y, Chen W J, Zhang Q, et al. BP neural network applied to 3D object measurement based on fringe pattern projection[J]. Opto-Electron Eng, 2007, 34(12): 61-65. doi: 10.3969/j.issn.1003-501X.2007.12.013

    CrossRef Google Scholar

    [3] Li B W, Zhang S. Superfast high-resolution absolute 3D recovery of a stabilized flapping flight process[J]. Opt Express, 2017, 25(22): 27270-27282. doi: 10.1364/OE.25.027270

    CrossRef Google Scholar

    [4] 范生宏, 刘昌儒, 亓晓彤, 等. 结构光三维测量系统精度分析及验证[J]. 光电工程, 2014, 41(5): 52-56. doi: 10.3969/j.issn.1003-501X.2014.05.009

    CrossRef Google Scholar

    Fan S H, Liu C R, Qi X T, et al. Accuracy analysis and verification of structured light 3D measurement system[J]. Opto-Electron Eng, 2014, 41(5): 52-56. doi: 10.3969/j.issn.1003-501X.2014.05.009

    CrossRef Google Scholar

    [5] 罗剑, 袁家虎. 光栅投影式三维摄影测量仪的几何标定方法[J]. 光电工程, 2005, 32(11): 43-48, 67. doi: 10.3969/j.issn.1003-501X.2005.11.012

    CrossRef Google Scholar

    Luo J, Yuan J H. Geometric calibration method of 3D photogrammetric instruments using grating projection[J]. Opto-Electron Eng, 2005, 32(11): 43-48, 67. doi: 10.3969/j.issn.1003-501X.2005.11.012

    CrossRef Google Scholar

    [6] Chen M Y, Tang Y C, Zhou X J, et al. High-accuracy multi-camera reconstruction enhanced by adaptive point cloud correction algorithm[J]. Opt Lasers Eng, 2019, 122: 170-183. doi: 10.1016/j.optlaseng.2019.06.011

    CrossRef Google Scholar

    [7] 苏显渝, 程晓雪, 郭履容. 三维物体360°面形自动测量方法[J]. 光学学报, 1989, 9(7): 670-672. doi: 10.3321/j.issn:0253-2239.1989.07.017

    CrossRef Google Scholar

    Su X Y, Cheng X X, Guo L R. An automated method for 360° surface measurement of 3-D objects[J]. Acta Opt Sin, 1989, 9(7): 670-672. doi: 10.3321/j.issn:0253-2239.1989.07.017

    CrossRef Google Scholar

    [8] 鲁亚楠, 万子敬, 王向军. 一种无公共视场相机位置关系的求解方法[J]. 应用光学, 2017, 38(3): 400-405.

    Google Scholar

    Lu Y N, Wan Z J, Wang X J. Solution to relative position of cameras without public FOV[J]. J Appl Opt, 2017, 38(3): 400-405.

    Google Scholar

    [9] Liu Z, Meng Z Z, Gao N, et al. Calibration of the relative orientation between multiple depth cameras based on a three-dimensional target[J]. Sensors(Basel), 2019, 19(13): 3008. doi: 10.3390/s19133008

    CrossRef Google Scholar

    [10] Besl P J, McKay N D. A method for registration of 3-D shapes[J]. IEEE Trans Pattern Anal Mach Intell, 1992, 14(2): 239-256. doi: 10.1109/34.121791

    CrossRef Google Scholar

    [11] 楚圣辉, 张慧萌, 陈硕, 等. 大场景下多目立体视觉标定方法的研究[J]. 现代计算机(专业版), 2017(15): 33-38.

    Google Scholar

    Chu S H, Zhang H M, Chen S, et al. Research on the calibration method of multi eye stereo vision in large scenes[J]. Mod Comput, 2017(15): 33-38.

    Google Scholar

    [12] 潘华伟, 杨振先, 高春鸣, 等. 一种基于平面模板的多摄像机标定方法[J]. 计算机应用研究, 2011, 28(11): 4357-4360. doi: 10.3969/j.issn.1001-3695.2011.11.096

    CrossRef Google Scholar

    Pan H W, Yang Z X, Gao C M, et al. Multi-camera calibration method using planar patterns[J]. Appl Res Comput, 2011, 28(11): 4357-4360. doi: 10.3969/j.issn.1001-3695.2011.11.096

    CrossRef Google Scholar

    [13] 郎威, 薛俊鹏, 李承杭, 等. 基于旋转台参数标定实现多视角点云拼接[J]. 中国激光, 2019, 46(11): 1104003.

    Google Scholar

    Lang W, Xue J P, Li C H, et al. Splicing of multi-view point clouds based on calibrated parameters of turntable[J]. Chinese J Lasers, 2019, 46(11): 1104003.

    Google Scholar

    [14] Zhang Z, Zhang D, Peng X. Performance analysis of a 3D full-field sensor based on fringe projection[J]. Opt Lasers Eng, 2004, 42(3): 341-353. doi: 10.1016/j.optlaseng.2003.11.004

    CrossRef Google Scholar

    [15] 周灿林, 司书春, 高成勇, 等. 基于格莱姆-施密特正交化两步相移轮廓术[J]. 光电工程, 2013, 40(6): 37-42. doi: 10.3969/j.issn.1003-501X.2013.06.007

    CrossRef Google Scholar

    Zhou C L, Si S C, Gao C Y, et al. Two-step phase-shifting profilometry based on Gram-Schmidt orthonormalization[J]. Opto-Electron Eng, 2013, 40(6): 37-42. doi: 10.3969/j.issn.1003-501X.2013.06.007

    CrossRef Google Scholar

    [16] Tsai R Y, Lenz R K. A new technique for fully autonomous and efficient 3D robotics hand/eye calibration[J]. IEEE Trans Robot Autom, 1989, 5(3): 345-358. doi: 10.1109/70.34770

    CrossRef Google Scholar

    [17] 毛剑飞, 邵黄芳, 蒋莉, 等. 求解方程RaRx=RxRb的四元数几何研究[J]. 中国图象图形学报, 2010, 15(6): 951-957. doi: 10.11834/jig.20100615

    CrossRef Google Scholar

    Mao J F, Shao H F, Jiang L, et al. Quaternion geometrical analysis on solving equation RaRx=RxRb[J]. J Image Graph, 2010, 15(6): 951-957. doi: 10.11834/jig.20100615

    CrossRef Google Scholar

    [18] 王昌云, 李立君. 基于四元数的机器人手眼标定算法[J]. 传感器与微系统, 2019, 38(12): 133-135.

    Google Scholar

    Wang C Y, Li L J. Hand-eye calibration algorithm for robot based on quaternion[J]. Transducer Microsyst Technol, 2019, 38(12): 133-135.

    Google Scholar

    [19] 胡为, 刘冲, 傅莉, 等. 一种高精度的机器人手眼标定算法[J]. 火力与指挥控制, 2018, 43(9): 19-24. doi: 10.3969/j.issn.1002-0640.2018.09.005

    CrossRef Google Scholar

    Hu W, Liu C, Fu L, et al. An algorithm for robot hand eye calibration with high accuracy[J]. Fire Control Comm Control, 2018, 43(9): 19-24. doi: 10.3969/j.issn.1002-0640.2018.09.005

    CrossRef Google Scholar

    [20] 魏振忠, 高明, 周富强, 等. 基于辅助摄像机的机器人延伸手眼标定方法[J]. 光电工程, 2008, 35(9): 76-80, 121. doi: 10.3969/j.issn.1003-501X.2008.09.016

    CrossRef Google Scholar

    Wei Z Z, Gao M, Zhou F Q, et al. Robot extended eye-in-hand calibration method based on an assistant camera[J]. Opto-Electron Eng, 2008, 35(9): 76-80, 121. doi: 10.3969/j.issn.1003-501X.2008.09.016

    CrossRef Google Scholar

  • Overview: The fringe projection measurement method is widely used in various fields due to its simple structure, high precision, and resolution, full field measurement, etc. The research on the single-view system of the fringe projection measurement method has been relatively mature. The dual-view fringe projection measurement system is an extension of the single-view fringe projection measurement system, a larger range of three-dimensional geometric information can be obtained by expanding the camera's field of view. In the dual-view fringe projection measurement system, the three-dimensional measurement results of the subsystem are always restored in the camera coordinate system, while the two camera coordinate systems are independent of each other in the dual-view fringe projection measurement system. Therefore, it is necessary to solve the transformation relationship between the two camera coordinate systems, the process of solving the transformation relationship between the two camera coordinate systems is called global calibration. Global calibration is the most important task in the calibration of dual and multi view systems. However, the existing global calibration methods require expensive auxiliary equipment when the two cameras have no common field of view, which adds a certain cost to the calibration, and when the viewing angle of the system is more than two, the method of relying on the auxiliary equipment is limited. Aiming at the limitations of the existing global calibration methods, this paper proposes a method to achieve dual-view global calibration by using two plane calibration boards: Firstly, through a series of derivation, the problem of solving the transformation matrix between the two camera coordinate systems is transformed into the problem of solving the hand-eye calibration equation which is more mature in the field of robot; Secondly, adjust the two calibration boards to the appropriate position according to the placement of the camera, and fix the two calibration boards; Thirdly, place the two calibration boards at several positions in the field of view of the two cameras at the same time to obtain several equations; Finally, the conversion matrix between the two cameras is obtained by using the quaternion method, least square method, and nonlinear optimization. The method identified in this paper does not require additional auxiliary equipment, and it is proved by quantitative experiments: this method can realize the calibration of dual cameras simultaneously and the absolute error of the method does not exceed 0.089 mm, which is relatively reliable; in the dual-view 3D measurement system, the cumulative error of global calibration and phase-depth does not exceed 0.116 mm, which can provide a reliable initial value for further data fusion. In addition, the global calibration method determined in this paper is suitable for multi-view 3D measurement systems. When the number of cameras is more than two, the calibration board corresponding to the number of cameras can be added to achieve simultaneous calibration of multiple cameras.

  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(10)

Tables(2)

Article Metrics

Article views(4078) PDF downloads(1378) Cited by(0)

Access History

Other Articles By Authors

Article Contents

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint