留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

重投影优化的自由双目相机位姿估计方法

陈天择 葛宝臻 罗其俊

陈天择, 葛宝臻, 罗其俊. 重投影优化的自由双目相机位姿估计方法[J]. 中国光学. doi: 10.37188/CO.2021-0105
引用本文: 陈天择, 葛宝臻, 罗其俊. 重投影优化的自由双目相机位姿估计方法[J]. 中国光学. doi: 10.37188/CO.2021-0105
CHEN Tian-ze, GE Bao-zhen, LUO Qi-jun. Pose estimation for free binocular cameras based on reprojection error optimization[J]. Chinese Optics. doi: 10.37188/CO.2021-0105
Citation: CHEN Tian-ze, GE Bao-zhen, LUO Qi-jun. Pose estimation for free binocular cameras based on reprojection error optimization[J]. Chinese Optics. doi: 10.37188/CO.2021-0105

重投影优化的自由双目相机位姿估计方法

doi: 10.37188/CO.2021-0105
基金项目: 国家自然科学基金项目(No. 61535008)
详细信息
    作者简介:

    陈天择(1995—),男,黑龙江哈尔滨人,硕士研究生,2018年于天津大学获得学士学位,现就读于天津大学精密仪器与光电子工程学院,攻读光学工程专业硕士学位,主要研究方向为计算机视觉。E-mail:chentianze@tju.edu.cn

    葛宝臻(1964—),男,内蒙古卓资人,博士,教授,博士生导师,主要从事三维彩色数字成像技术、光电检测技术、激光粒子测量方面的研究。E-mail:gebz@tju.edu.cn

    罗其俊(1982—),男,湖北孝感人,博士,2008年于中国民航大学获得硕士学位,现为中国民航大学电子信息与自动化学院讲师,主要从事机器视觉和只能控制系统方面的研究。E-mail:qjluo@cauc.edu.cn

  • 中图分类号: TP391.4

Pose estimation for free binocular cameras based on reprojection error optimization

Funds: Supported by National Natural Science Foundation of China (No. 61535008)
  • 摘要: 在自由双目立体视觉系统中,左右相机自由旋转,导致相机位姿发生实时变化。针对这一问题,提出一种重投影优化的自由双目相机位姿估计方法。通过分解相邻两幅图像间的单应矩阵估计相机的运动参数;将其作为初值计算重叠拍摄区域内特征点云的重投影误差,构建目标函数;利用非线性优化算法优化目标函数,得到最优的相机运动参数,结合相机旋转前的位姿参数,计算当前位置的相机位姿。仿真实验表明,位姿估计误差随重投影误差的减小而减小,所提算法能快速稳定收敛至全局最优值;水泥模型的三维重建实验表明,利用所提的相机位姿估计算法能够有效生成模型的三维点云,并可实现相邻点云的高精度拼接,拼接点云模型上两点距离的平均误差为1.68%。
  • 图  1  自由双目立体视觉系统中相邻两次测量

    Figure  1.  Two adjacent measurements of the free binocular vision system

    图  2  位姿估计误差随重投影误差的变化

    Figure  2.  Changes in pose estimation error with reprojection error

    图  3  不同条件下算法的收敛情况

    Figure  3.  Convergence of the algorithm under various conditions

    图  4  不同参考点数目对算法的影响

    Figure  4.  Changes to the algorithm with different numbers of reference points

    图  5  不同噪声对算法的影响

    Figure  5.  Changes to the algorithm under different noise

    图  6  自由双目立体视觉装置图

    Figure  6.  Device diagram of free binocular stereo vision

    图  7  双目相机采集图像

    Figure  7.  Images obtained by binocular cameras

    图  8  三维重建结果

    Figure  8.  3D reconstruction results

    表  1  标志点间距(单位:mm)

    Table  1.   Distance between mark points(Unit: mm)

    实验次数 AB间距 CD间距 EF间距
    1 498.073 199.762 501.328
    2 501.137 197.037 501.670
    3 500.569 198.053 502.404
    4 502.842 200.459 502.634
    下载: 导出CSV
    ag币游app_币游娱乐官网(官网推荐)
  • [1] 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 SH Z, LI X X, SUN ZH CH. Novel design of low cost mobile robot lazer scanner[J]. Computer Measurement &Control, 2011, 19(5): 1094-1097. (in Chinese)
    [2] 李肖, 葛宝臻, 罗其俊, 等. 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. doi: 10.11772/j.issn.1001-9081.2017.10.2888

    LI X, GE B ZH, LUO Q J, et al. Acquisition of camera dynamic extrinsic parameters in free binocular stereo vision system[J]. Journal of Computer Applications, 2017, 37(10): 2888-2894. (in Chinese) doi: 10.11772/j.issn.1001-9081.2017.10.2888
    [3] 于海, 万秋华, 孙莹, 等. 一种自适应安装的高精度图像式角位移测量装置[J]. 中国光学,2020,13(3):510-516.

    YU H, WAN Q H, SUN Y, et al. A high precision image angular displacement measurement device with self-adaptive installation[J]. Chinese Optics, 2020, 13(3): 510-516. (in Chinese)
    [4] SWEENEY C, SATTLER T, H?LLERER T, et al.. Optimizing the viewing graph for structure-from-motion[C]. 2015 IEEE International Conference on Computer Vision (ICCV), IEEE, 2015: 801-809.
    [5] MOULON P, MONASSE P, MARLET R. Global fusion of relative motions for robust, accurate and scalable structure from motion[C]. 2013 IEEE International Conference on Computer Vision, IEEE, 2013: 3248-3255.
    [6] ZHU S Y, ZHANG R Z, ZHOU L, et al.. Very large-scale global SfM by distributed motion averaging[C]. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2018: 4568-4577.
    [7] ZHUANG B B, CHEONG L F, LEE G H. Baseline desensitizing in translation averaging[C]. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2018: 4539-4547.
    [8] NISTER D. An efficient solution to the five-point relative pose problem[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(6): 756-770. doi: 10.1109/TPAMI.2004.17
    [9] 杜瑞建, 葛宝臻, 陈雷. 多视高分辨率纹理图像与双目三维点云的映射方法[J]. 中国光学,2020,13(5):1055-1064. doi: 10.37188/CO.2020-0034

    DU R J, GE B ZH, CHEN L. Texture mapping of multi-view high-resolution images and binocular 3D point clouds[J]. Chinese Optics, 2020, 13(5): 1055-1064. (in Chinese) doi: 10.37188/CO.2020-0034
    [10] SNAVELY N, SEITZ S M, SZELISKI R. Photo tourism: exploring photo collections in 3D[J]. ACM Transactions on Graphics, 2006, 25(3): 835-846. doi: 10.1145/1141911.1141964
    [11] WU CH CH. Towards linear-time incremental structure from motion[C]. 2013 International Conference on 3D Vision - 3DV 2013, IEEE, 2013: 127-134.
    [12] SCHONBERGER J L, FRAHM J M. Structure-from-motion revisited[C]. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2016: 4104-4113.
    [13] LEPETIT V, MORENO-NOGUER F, FUA P. EPnP: an accurate O(n) solution to the PnP problem[J]. International Journal of Computer Vision, 2009, 81(2): 155-166. doi: 10.1007/s11263-008-0152-6
    [14] PENATE-SANCHEZ A, ANDRADE-CETTO J, MORENO-NOGUER F. Exhaustive linearization for robust camera pose and focal length estimation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(10): 2387-2400. doi: 10.1109/TPAMI.2013.36
    [15] 李正炜, 王建立, 吴元昊, 等. 基于单站地基望远镜的空间目标姿态估计方法[J]. 中国光学,2016,9(3):371-378. doi: 10.3788/co.20160903.0371

    LI ZH W, WANG J L, WU Y H, et al. Method of attitude estimation for space object based on single ground-based telescope[J]. Chinese Optics, 2016, 9(3): 371-378. (in Chinese) doi: 10.3788/co.20160903.0371
    [16] ENGEL J, SCH?PS T, CREMERS D. LSD-SLAM: large-scale direct monocular SLAM[C]. Proceedings of the 13th European Conference, Springer, 2014: 834-849.
    [17] 张可, 杨灿坤, 周春平, 等. 无人机视频图像运动目标检测算法综述[J]. 液晶与显示,2019,34(1):98-109. doi: 10.3788/YJYXS20193401.0098

    ZHANG K, YANG C K, ZHOU CH P, et al. Review of moving target detection algorithms for UAV video images[J]. Chinese Journal of Liquid Crystals and Displays, 2019, 34(1): 98-109. (in Chinese) doi: 10.3788/YJYXS20193401.0098
    [18] LI Y Y, BRASCH N, WANG Y D, et al. Structure-SLAM: low-drift monocular SLAM in indoor environments[J]. IEEE Robotics and Automation Letters, 2020, 5(4): 6583-6590. doi: 10.1109/LRA.2020.3015456
    [19] CUI H N, SHEN SH H, GAO X, et al.. Batched incremental structure-from-motion[C]. 2017 International Conference on 3D Vision (3DV), IEEE, 2017: 205-214.
    [20] 周单, 董秀成, 张帆, 等. 基于自适应重投影误差单目位姿优化算法[J]. 激光与光电子学进展,2019,56(2):021204.

    ZHOU D, DONG X CH, ZHANG F, et al. Monocular pose optimization algorithm based on adaptive reprojection error[J]. Laser &Optoelectronics Progress, 2019, 56(2): 021204. (in Chinese)
    [21] 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

    ZHAO Y F, HU J F. Binocular self calibration using two pairs of orthogonal vanishing points[J]. Chinese Journal of Liquid Crystals and Displays, 2016, 31(10): 958-966. (in Chinese) doi: 10.3788/YJYXS20163110.0958
    [22] HARTLEY R, ZISSERMAN A. Multiple View Geometry in Computer Vision[M]. 2nd ed. Cambridge: Cambridge University Press, 2003.
  • 加载中
图(8) / 表(1)
计量
  • 文章访问数:  85
  • HTML全文浏览量:  37
  • PDF下载量:  9
  • 被引次数: 0
出版历程
  • 网络出版日期:  2021-08-11

目录

    /

    返回文章
    返回