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浙江大学学报(工学版)
浙江大学学报(工学版)  2018, Vol. 52 Issue (12): 2372-2381    DOI: 10.3785/j.issn.1008-973X.2018.12.016
计算机技术     
单目序列的刚体目标位姿测量
赵丽科1,2, 郑顺义1,3, 王晓南1, 黄霞1
1. 武汉大学 遥感信息工程学院, 湖北 武汉 430079;
2. 河南工业大学 信息科学与工程学院, 河南 郑州 450001;
3. 武汉大学 地球空间信息技术协同创新中心, 湖北 武汉 430079
Rigid object position and orientation measurement based on monocular sequence
ZHAO Li-ke1,2, ZHENG Shun-yi1,3, WANG Xiao-nan1, HUANG Xia1
1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
2. College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China;
3. Collaborative Innovation Center for Geospatial Technology, Wuhan University, Wuhan 430079, China
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摘要：

针对单目相机不具备构建合作目标的情况及其对平面上运动目标位姿测量的应用需求，提出一种基于目标轮廓的运动目标位姿自动解算方法.该方法以目标三维几何模型和相机参数作为先验信息，利用OpenGL生成位于不同位姿的运动目标模拟图像，通过模拟图像与实拍图像之间的关系进行位姿的求解.首先由离散位姿集合的模拟图像得到运动目标轮廓集合，由实拍图像运动目标轮廓与离散位姿轮廓集合中轮廓间的关系确定运动目标的初始位姿.然后构建初始位姿下模拟图像的目标轮廓与实拍图像目标轮廓间的距离代价函数，采用非线性优化算法迭代求解运动目标的精确位姿.实验结果表明，提出的方法可以有效地测量运动目标的位姿，且当图像中纹理复杂、受阴影影响时仍能取得较好的测量结果.
Abstract:

An automatic method for the position and orientation achievement of moving object based on contour was proposed, since the monocular camera cannot construct the cooperative target and the position and orientation measurement to the moving object on the plane is required. The proposed method was under the prior condition of three-dimensional geometric model of the rigid object and the camera parameters. OpenGL technology was used to generate the simulated images of the moving objects located in different positions and orientations. The position and orientation were solved by the relationship between the simulated images and the real images. Firstly, the moving object contour set was obtained according to the simulation of discrete position and orientation sets, and the initial position and orientation of the moving object was determined from the relationship between the moving object contour of real image and the contour in the discrete position and orientation contour set. Then, the distance cost function between the object contour of the simulated image of initial value and the object contour of the real image was constructed, and the precise position and orientation of the moving object was solved by iterative nonlinear optimization algorithm. The experimental results show that the proposed method can effectively measure the position and orientation of the moving object, and obtain reliable measurement results of the image with complex texture and shadow.
收稿日期: 2017-11-23 出版日期: 2018-12-13
CLC:  TP391  
基金资助:

国家自然科学基金资助项目（41671452，41701532）；河南工业大学高层次人才科研基金资助项目（2018BS054）；中央高校基本科研业务费专项资助项目（2042016kf0012）；中国博士后科学基金资助项目（2017M612510）
通讯作者: 郑顺义,男,教授.orcid.org/0000-0001-5594-3493.     E-mail: syzheng@whu.edu.cn
作者简介: 赵丽科(1990-),女,讲师,博士,从事数字摄影测量研究.orcid.org/0000-00003-2799-1978.E-mail:lenci_zhao@whu.edu.cn
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引用本文:

赵丽科, 郑顺义, 王晓南, 黄霞. 单目序列的刚体目标位姿测量[J]. 浙江大学学报(工学版), 2018, 52(12): 2372-2381.

ZHAO Li-ke, ZHENG Shun-yi, WANG Xiao-nan, HUANG Xia. Rigid object position and orientation measurement based on monocular sequence. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(12): 2372-2381.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2018.12.016    或    http://www.zjujournals.com/eng/CN/Y2018/V52/I12/2372

[1] LI J, BESADA J A, BERNARDOS A M. A novel system for object pose estimation using fused vision and inertial data[J]. Information Fusion, 2017, 33(C):15-28.
[2] SHARMA S, D'AMICO S. Comparative assessment of techniques for initial pose estimation using monocular vision[J]. Acta Astronautica, 2016, 123(1-2):435-445.
[3] WANG X, YU H, FENG D. Pose estimation in runway end safety area using geometry structure features[J]. Aeronautical Journal, 2016, 120(1226):675-691.
[4] D'AMICO S, BENN M, JØRGENSEN J L. Pose estimation of an uncooperative spacecraft from actual space imagery[J]. International Journal of Space Science and Engineering, 2013(2):171-189.
[5] 陈娟, 陈乾辉. 空间目标三维姿态估计方法综述[J]. 长春工业大学学报:自然科学版, 2008, 29(3):323-327 CHEN Juan, Chen Qian-hui. Summary of the 3D pose estimations for the space targets[J]. Journal of Changchun University of Technology:Natural Science Edition, 2008, 29(3):323-327
[6] 肖旭. 单目视觉位姿测量方法的研究[D]. 天津:天津大学, 2009. XIAO Xu. Study on the monocular vision measurement method[D]. Tianjin:Tianjin University, 2009.
[7] PAN H, HUANG J Y, QIN S Y. Relative pose estimation under monocular vision in rendezvous and docking[J]. Applied Mechanics and Materials, 2013, 433-435:799-805.
[8] DEMENTHON D F, DAVIS L S. Model-based object pose in 25 lines of code[J]. International Journal of Computer Vision, 1995, 15(1/2):123-141.
[9] GUO Z, LI Z, ZHANG D, et al. Research on pose estimation method for cooperative target based on monocular images[C]//20116th IEEE Conference on Industrial Electronics and Applications (ICIEA). Beijing:IEEE, 2011:547-552.
[10] ÉRIC M, PATRICK B, FRANÇOIS C. A 2D-3D model-based approach to real-time visual tracking[J]. Image and Vision Computing, 2001, 19(13):941-955.
[11] ROMEIL S, SAMUEL D, ANTHONY Y, et al. A nonrigid kernel-based framework for 2D-3D pose estimation and 2D image segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(6):1098-1115.
[12] 宋薇, 周扬. 基于CAD模型的单目六自由度位姿测量[J]. 光学精密工程, 2016, 24(4):882-891 SONG Wei, ZHOU Yang. Estimation of monocular vision 6-DOF pose based on CAD model[J]. Optics and Precision Engineering, 2016, 24(4):882-891
[13] 吴立新, 王植, 孔祥勤. 盲环境移动定位(Ⅱ):基于单目视觉系统的定位技术[J]. 东北大学学报:自然科学版, 2011, 32(5):736-739 WU Li-xin, WANG Zhi, KONG Xiang-qin. Mobile positioning in blind environments (Ⅱ):positioning moving targets based on a monocular vision system[J]. Journal of Northeastern University:Natural Science, 2011, 32(5):736-739
[14] PAN H, HUANG J, QIN S. High accurate estimation of relative pose of cooperative space targets based on measurement of monocular vision imaging[J]. Optik-International Journal for Light and Electron Optics, 2014, 125(13):3127-3133.
[15] 童张海. 单目视觉空间目标位姿测量算法研究[D]. 哈尔滨:哈尔滨工业大学, 2012. TONG Zhang-hai. Alogrithm of relative pose estimation for space target based on monocular-vision[D]. Harbin:Harbin Institute of Technology, 2012.
[16] IWASHITA Y, KURAZUME R, HASEGAWA T, et al. Fast alignment of 3D geometrical models and 2D color images using 2D distance maps[C]//International Conference on 3D Digital Imaging and Modeling. Ottawa:IEEE Computer Society, 2005:164-171.
[17] LENG D W, SUN W D. Iterative three-dimensional rigid object pose estimation with contour correspondence[J]. IET Image Processing, 2012, 6(5):569-579.
[18] ROSENHAHN B, BROX T, WEICKERT J. Three-Dimensional shape knowledge for joint image segmentation and pose tracking[J]. International Journal of Computer Vision, 2007, 73(3):243-262.
[19] PAPARI G, PETKOV N. Edge and line oriented contour detection:state of the art[J]. Image and Vision Computing, 2011, 29(2-3):79-103.
[20] DELAMARRE Q, FAUGERAS O. 3D articulated models and multi-view tracking with silhouettes[C]//IEEE International Conference on Computer Vision. Kerkyra:IEEE, 1999:716-721.
[21] POWELL M J. Developments of NEWUOA for minimization without derivatives[J]. IMA Journal of Numerical Analysis, 2008, 28(4):649-664.
[22] POWELL M J. Beyond symmetric Broyden for updating quadratic models in minimization without derivatives[J]. Mathematical Programming, 2013, 138(1/2):475-500.
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