期刊文献+

基于整体最小二乘的稳健点云数据平面拟合 被引量:68

ROBUST PLANE FITTING OF POINT CLOUDS BASED ON TLS
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摘要 针对点云数据平面拟合方法没有完整考虑测量数据中的误差及系数阵中误差的情况,提出稳健整体最小二乘点云数据平面拟合方法。该法以整体最小二乘法为基础,在考虑全部观测量存在误差的情况下,通过一定的准则删除数据中的粗差或异常值,从而获得稳健的平面参数估值。实验中,分别利用最小二乘法、特征值法和稳健整体最小二乘拟合法对仿真点云数据和真实点云数据进行平面拟合,结果显示该法能克服异常值的影响,得到可靠的平面参数估值,具有稳健性。 In traditional plane fitting methods for point clouds,people don’t consider errors in data and in coefficients matrix simultaneously,which will result in incorrectness of plane parameters.In order to overcome this shortcoming,a new method for fitting local plane to point clouds was proposed.The method is based on total least squares.In consideration of the errors in all observation data,we tried to delete outliers from point clouds,and thus obtained a robust solution to plane fitting parameter.Analytical experiments based on simulated data and real data were conducted,and comparisons between the method and traditional methods such as least square method and eigenvalue method were also implemented.The results show that the method has the capability to overcome bad influence from outliers,and to increase the reliability of parameters estimation.
出处 《大地测量与地球动力学》 CSCD 北大核心 2011年第5期80-83,共4页 Journal of Geodesy and Geodynamics
基金 国家自然科学基金(40874010) 江西省自然科学基金(2008GQC0001 2010GZC0009 2010GZC0008) 地球空间环境与大地测量教育部重点实验室开放基金(10-01-06)
关键词 点云数据 整体最小二乘 平面拟合 异常值 稳健性 point clouds Total Least Squares (TLS) plane fitting outliers robustness
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参考文献9

  • 1罗德安,朱光,陆立,廖丽琼.基于3维激光影像扫描技术的整体变形监测[J].测绘通报,2005(7):40-42. 被引量:154
  • 2Prabhat K Acharya, et al. Parameter estimation and error analysis of range data [ B/OL ]. http :// ieee - xplore, ieee. org/xpls/abs_all, jsp? arnumber = 12312, 2002.8.
  • 3何文峰,查红彬.基于平面特征的深度图像配准[A].见:中国人工智能进展2003,上卷[C]:643-648,北京邮电大学出版社,2003.
  • 4Wang Caihua, et. al. Comparison of local plane fitting methods for range data [ B/OL]. http://ieeexplore, ieee. org/ xpls/abs_all jsp? arnumber =990538,2003.4.
  • 5官云兰,程效军,施贵刚.一种稳健的点云数据平面拟合方法[J].同济大学学报(自然科学版),2008,36(7):981-984. 被引量:117
  • 6Golub G H and Lan Loan F C. An analysis of the total least squares problem[ J ].SIAM Journal on Numerical Analysis, 1980, 17(6) : 883-893.
  • 7Burkhard Schaffrin. A note on constrained total least squares estimation[ J ]. Linear Algebra and its Application,2006, (417) : 245 -258.
  • 8鲁铁定,周世健,张立亭,官云兰.基于整体最小二乘的地面激光扫描标靶球定位方法[J].大地测量与地球动力学,2009,29(4):102-105. 被引量:44
  • 9张贤达.矩阵分析与应用[M].北京:清华大学出版社,2008:268-271.

二级参考文献21

  • 1高山.I-SITE 3D激光成像系统在矿山勘测工程中的应用研究[J].科技进步与对策,2003,20(S1):293-294. 被引量:1
  • 2刘旭春,丁延辉.三维激光扫描技术在古建筑保护中的应用[J].测绘工程,2006,15(1):48-49. 被引量:122
  • 3Lai J Y, Ueng W D and Yao C Y. Registration and data merging for multiple sets of scan data [ J ]. The International Journal of Advanced Manufacturing Technology, 1999, 15 (1) :54 -63.
  • 4Craig M and Shakarji. Least - squares fitting algorithms of the NIST algorithm testing system [ J]. Journal of research of the National Institute of Standards and Technology, 1998, 103:633 - 641.
  • 5Yuriy Reshetyuk,Milan Horemuz and Lars E Sjoberg. Determination of the optimal diameter for spherical targets used in 3D laser scanning [ J ]. Survey Review, 2005,38 ( 297 ) : 243 - 253.
  • 6Burkhard Schaffrin. A note on constrained total least - squares estimation [ J ]. Linear Algebra and its Applications,2006, ( 417 ) : 245 - 258.
  • 7Golub G H and Van Loan C F. An analysis of the total least squares problem[ J]. SIAM J Numer. Anal, 1980,17:883 - 893.
  • 8LOVELL J L, JUPP D L B, CULVENOR D S, et al.Using Airborne and Ground-based Ranging Lidar to Measure Canopy Structure in Australian Forests[J]. Can. J.Remote Sensing, 2003, 29, (5):607-622.
  • 9JUPP D L B, STRAHLER A H, WOODCOCK C E.Autocorrelation and Regularization in Digital Images. Ⅱ.Simple Image Models[J]. IEEE Transactions on Geoscience and Remote Sensing, 1989,27: 247-258.
  • 10何文峰,查红彬.基于平面特征的深度图像配准[C]//中国人工智能进展2003.北京:北京邮电大学出版社,2003:643-648.

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