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基于球面特征的点云配准方法研究

张学昌 唐艳梅 梁涛

张学昌, 唐艳梅, 梁涛. 基于球面特征的点云配准方法研究[J]. 机械科学与技术, 2015, 34(12): 1851-1856. doi: 10.13433/j.cnki.1003-8728.2015.1209
引用本文: 张学昌, 唐艳梅, 梁涛. 基于球面特征的点云配准方法研究[J]. 机械科学与技术, 2015, 34(12): 1851-1856. doi: 10.13433/j.cnki.1003-8728.2015.1209
Zhang Xuechang, Tang Yanmei, Liang Tao. Research on Registration Method of Point Clouds Based on Spherical Feature[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(12): 1851-1856. doi: 10.13433/j.cnki.1003-8728.2015.1209
Citation: Zhang Xuechang, Tang Yanmei, Liang Tao. Research on Registration Method of Point Clouds Based on Spherical Feature[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(12): 1851-1856. doi: 10.13433/j.cnki.1003-8728.2015.1209

基于球面特征的点云配准方法研究

doi: 10.13433/j.cnki.1003-8728.2015.1209
基金项目: 

国家自然科学基金项目(51075362)、浙江省自然科学基金项目(Y1100073)及宁波市产业技术创新及成果产业化重点项目(2013B10022)资助

详细信息
    作者简介:

    张学昌(1969-),教授,研究方向为机械工程,逆向工程,zz_zxc123@163.com

Research on Registration Method of Point Clouds Based on Spherical Feature

  • 摘要: 针对多视点云的配准问题,提出了基于球面特征的自动配准方法。在测量的零件周围固定标准球,把零件和标准球作为一个整体进行点云测量。用球面拟合的方法求解标准球的球心坐标,并在待配准点云的球心坐标中搜索对应点,从而计算粗配准中的旋转矩阵和平移矩阵,实现点云的粗配准,采用融入球心坐标信息的改进的ICP算法(迭代最近点法)实现点云的精配准。这种方法大大缩少了粗配准中对应点的搜索范围,并实现了自动配准,提高了配准效率,改进的ICP算法增强了配准算法的鲁棒性,实例证明该方法有效。
  • [1] Salvi J, Matabosch C, Fofi D, et al. A review of recent range image registration methods with accuracy evaluation[J]. Image and Vision Computing, 2007,25(5):578-596
    [2] Hecker Y C, Bolle R M. On geometric hashing and the generalized hough transform[J]. IEEE Transactions on Systems, Man and Cybernetics, 1994,24(9):1328-1338
    [3] Wolfson H J, Rigoutsos I. Geometric hashing: an overview[J]. IEEE Computer Science & Engineering, 1997:10-21
    [4] Stockman G. Object recognition and localization via pose clustering[J]. Computer Vision, Graphics, and Image Processing, 1987,40(3):361-387
    [5] Johnson A E. Spin-images: a representation for 3-D surface matching[D]. Pittsburgh, USA: Carnegie Mellon University, 1997
    [6] Lee J D, Huang C H, Liu L C, et al. A modified soft-shape-context ICP registration system of 3-D point data[J]. IEICE Transactions on Information and Systems, 2007,E90-D(12):2087-2095
    [7] Chua C S, Jarvis R. Point signatures: a new representation for 3D object recognition[J]. International Journal of Computer Vision, 1997,25(1):63-85
    [8] Salvi J, Matabosch C, Fofi D, et al. A review of recent range image registration methods with accuracy evaluation[J]. Image and Vision Computing, 2007,25(5):578-596
    [9] Gelfand N. Feature analysis and registration of scanned surfaces[D]. Palo Alto, California: Stanford University, 2006
    [10] Besl P J, McKay N D. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992,14(2):239-256
    [11] Rusinkiewicz S, Levoy M. Efficient variants of the ICP algorithm[C]//Proceedings of the Third International Conference on 3-D Digital Imaging and Modeling, Quebec City, Que: IEEE, 2001:145-152
    [12] Turk G, Levoy M. Zippered polygon meshes from range images[C]//Proceedings of ACM SIGGRAPH. Orlando, Florida: ACM, 1994:311-318
    [13] Masuda T, Sakaue K, Yokoya N. Registration and integration of multiple range images for 3-D model construction[C]//Proceedings of the 13th International Conference on Pattern Recognition. Vienna: IEEE, 1996:879-883
    [14] Jost T. Fast geometric matching for shape registration[D]. Neuchatel, Switzerland: University of Neuchatel, 2002
    [15] 熊邦书,何明一,俞华璟.三维散乱数据的k个最近邻域快速搜索算法[J].计算机辅助设计与图形学学报,2004,16(7):909-912,917 Xiong B S, He M Y, Yu H J. Algorithm for finding k-nearest neighbors of scattered points in three dimensions[J]. Journal of Computer Aided Design & Computer Graphics, 2004,16(7):909-912,917 (in Chinese)
    [16] 刘越华,廖文和,刘浩.逆向工程中散乱点云的K邻域搜索算法研究[J].机械设计与制造,2012,(3):256-258 Liu Y H, Liao W H, Liu H. Research of k-nearest neighbors search algorithm in reverse engineering[J]. Machinery Design & Manufacture, 2012,(3):256-258 (in Chinese)
    [17] 陈曦.反求工程中基于点云的特征挖掘技术研究[D].杭州:浙江大学,2005 Chen X. Based on point cloud feature mining technology in reverse engineering[D]. Hangzhou: Zhejiang University, 2005 (in Chinese)
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出版历程
  • 收稿日期:  2014-02-28
  • 刊出日期:  2015-12-05

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