一种假肢膝关节测量系统的标定方法
A Method of Calibration of A Prosthetic Knee Joint Measurement System
DOI: 10.12677/OE.2017.73013, PDF, HTML, XML, 下载: 1,367  浏览: 3,378 
作者: 龚 喆, 鞠 鑫, 刘丙才：西安工业大学光电工程学院，陕西 西安
关键词: 三维重建；激光三角法；相机系统标定；3D Reconstruction； Laser Triangulation； Camera System Calibration
摘要: 激光三角法是一种传统的非接触式的三维轮廓测量方法，在物体的轮廓测量方面有着其独特的优势。本文基于对假肢膝关节面的研究，针对假肢膝关节面的特点，建立了基于激光三角法的三维轮廓测量系统，提出了基于棋盘格的测量系统标定方法；利用线激光、精密旋转台和CCD摄像机搭建了假肢膝关节面测量系统，通过理论分析、图像数据采集、角点检测等一系列过程获得了假肢膝关节面测量系统的标定数据，包括旋转矩阵和平移向量，这一标定方法为假肢膝关节面的三维轮廓重建奠定了基础。对该假肢膝关节的三维重构打下基础。并且针对传统的激光三角法的相机标定进行简要分析，提出了一种简易的激光三角法的相机系统标定方案。由于这种方案结构简单，易于分析，使用灵活方便等优点，因此具有广泛的发展空间和应用前景。
Abstract: The laser triangulation method is a traditional non-contact three-dimensional contour measurement method, which has its unique advantages in contour measurement of objects. Based on the study of prosthetic knee joint surface, the laser triangulation method and the camera system calibration scheme proposed in this paper are used to construct the experimental platform of prosthetic knee joint measurement. The three-dimensional coordinates of the prosthetic knee joint are obtained. The three-dimensional reconstruction of prosthetic knee joint laid the foundation. And a brief analysis of the camera calibration of the traditional laser triangulation method is proposed, and a simple laser triangulation camera system calibration scheme is proposed. Because of the simple structure of this scheme, easy to analyze, the use of flexible and convenient advantages, it has a wide range of development space and application prospects.
文章引用：龚喆, 鞠鑫, 刘丙才. 一种假肢膝关节测量系统的标定方法[J]. 光电子, 2017, 7(3): 87-94. https://doi.org/10.12677/OE.2017.73013

参考文献

[1] Rusinkiewicz, S. and Levoy, M. A Multi-resolution Point Rendering System for Large Meshes. International Conference on Computer Graphics and Interactive Techniques, New Orleans, 16-19 December 2000, 343-352.
[2] Huang, C.C. (1997) Efficient Digitizing of Sculptured Surfaces. Doctor’s Thesis. The Ohio State University, Columbus.
[3] Wallace, A.M., Zhang, G. and Gallaher, Y. (1998) Scan Calibration or Compensation in A Depth Hanging System. Pattern Recognition Letters, 19, 605-612.
https://doi.org/10.1016/S0167-8655(98)00040-3
[4] Xi, F., Liu, Y. and Feng, H.Y. (2001) Error Compensation for Three-dimensional Line Laser Scanning Data. The International Journal of Advanced Manufacturing Technology, 18, 211-216.
https://doi.org/10.1007/s001700170076
[5] Hakim, S.F.E., Brenner, C. and Roth, G.A. (1998) Multi-Sensor Approach to Creating Accurate Virtual Environments. Journal of Photogrammetry and RemoteSensing, 53, 379-391.
https://doi.org/10.1016/S0924-2716(98)00021-5
[6] Zhao, H. and Shibasaki, R. (1999) A System for Reconstructing Urban 3D Objects Using Ground-based Range and CCD Sensors. Proceedings of International Workshop on Urban Multi-Media/3D Mapping, 54, 1-22.
[7] Allen, P.K. and Stamos, I. (2003) 3D Modeling of Historic Sites Using Range and Image Data. International Conference of Robotics and Automation, Taipei, 14-19 September 2003, 145-150.
https://doi.org/10.1109/ROBOT.2003.1241587
[8] Simon, W. and Sven, M. (2006) Low-Cost Laser Range Scanner and Fast Surface Registration Approach. Springer, Berlin, 718-728.
[9] 马颂德, 张正友. 计算机视觉理论与算法基础[M]. 北京: 科学出版社, 1998.
[10] 李中伟, 王从军, 史玉升. 测量系统中的高精度摄像机标定算法[J]. 光电工程, 2008, 35(4): 58-63.
[11] 邹凤娇. 摄像机标定及相关技术研究[D]: [硕士学位论文]. 成都: 四川大学, 2005.
[12] Hartley, R. and Zisserman, A. 计算机视觉中的多视图几何[M]. 韦穗, 杨尚骏, 章权兵, 胡茂林, 译. 合肥: 安徽大学出版社, 2002.

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