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三维重建中的点云配准方法研究 被引量:1

Point-cloud Registration in 3D Reconstruction
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摘要 对序列点云拼接实现三维场景重建的方法进行研究,在重建方法中引入体积空间映射方法,有效地去除了拼接结果中的重复点、并填补了空洞。提出了改进的ICP算法和体积空间融合算法相结合的三维重建方法。实验证明该方法能有效地提高拼接结果的精度。 3D reconstruction based on point-cloud sequence is studied,and overlapping points are effectively removed and holes are filled by adding Volume space mapping in this 3D reconstruction method.A new 3D reconstruction method which combines efficient variant ICP algorithm and Volume space mapping,is depicted.The experiments show that the precision of point-cloud registration can be improved by using this method.
作者 杨彪 王卓
出处 《计算机与数字工程》 2014年第2期300-303,327,共5页 Computer & Digital Engineering
关键词 三维重建 ICP 体积空间融合 3D reconstruction ICP volume space mapping
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参考文献15

  • 1刘繁明,屈昊.ICP算法的鲁棒性改进[J].仪器仪表学报,2004,25(z1):603-605. 被引量:5
  • 2郑德华.ICP算法及其在建筑物扫描点云数据配准中的应用[J].测绘科学,2007,32(2):31-32. 被引量:60
  • 3Paul J Besl,Neil D Mckay.A Method for Registration of 3-D Shapes[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1992(2).
  • 4Rusinkiewicz S,Levoy M.A mul-tiresolution point rendering system for large meshes[C] //International Conference on Computer Graphics and Interactive Techniques,New Orleans,2000:343-352.
  • 5Brian Curless,Marc Levoy.A Volumetric Method for Building Complex Models from Range Image[C] //Proceedings of the 23rd annual conference on Computer graphics and interactive techniques,ACM New York,1996:303-312.
  • 6周春艳,李勇,邹峥嵘.三维点云ICP算法改进研究[J].计算机技术与发展,2011,21(8):75-77. 被引量:48
  • 7苏胜利,项志宇.基于二维激光雷达的自动室内三维重建系统[J].传感技术学报,2007,20(5):985-989. 被引量:9
  • 8Stamos I,Allen P K.Geometry and texture recovery of scenes of large scale[J].Computer Vision and Image Understanding,2002,8 (2):94-118.
  • 9Allen P K.Stamos L 3D modeling of historic sites using range and image data[C] //International Conference of Robotics and Automation,Taipei,2003:145-150.
  • 10郭杨.基于三维激光测量系统的点云拼接理论与试验研究[D].上海:上海交通大学,2012,2:430-434.

二级参考文献58

共引文献159

同被引文献24

  • 1沈海平,达飞鹏,雷家勇.基于最小二乘法的点云数据拼接研究[J].中国图象图形学报,2005,10(9):1112-1116. 被引量:28
  • 2Kumari P, Shrestha R, Carter B. Registration of LiDAR data through stable surface matching[C]. Geoinformatics, 2009 17th International Conference on IEEE, 2009. 1-5.
  • 3Grant W S, Voorhies R C, Itti L. Finding planes in LiDAR point clouds for real-time registration[C]. Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on IEEE, 2013. 4347-4354.
  • 4M Magnusso distributions Magnusson n, H Andreasson, A Ntichter, et al.. Automatic appearance-based loop detection from 3D laser data using the normal M, Lilienthal Journal of Field Robotics, 2009, 26(11-12): 892-914.
  • 5A, Duckett T. Scan registration for autonomous mining vehicles using 3D-NDT[J]. Journal of Field Robotics, 2007, 24(10): 803-827.
  • 6Liang Y B, Zhan Q M, Che E Z, et al.. Automatic registration of terrestrial laser scanning data using precisely located artificial planar targets[J]. Geoscience and Remote Sensing Letters, IEEE, 2014, 11 (1): 69-73.
  • 7Cao Y, Yang M Y, McDonald J. Robust alignment of wide baseline terrestrial laser scans via 3d viewpoint normalization[C]. Applications of Computer Vision (WACV) IEEE, 2011. 455-462.
  • 8解则晓,徐尚.三维点云数据拼接中ICP及其改进算法综述[J].中国海洋大学学报(自然科学版),2010,40(1):99-103. 被引量:58
  • 9王蒙,隋立春,黎恒明.机载LiDAR点云数据的航带拼接研究探讨[J].测绘通报,2010(7):5-8. 被引量:8
  • 10邢正全,邓喀中.一种改进的点云数据配准方法[J].测绘工程,2011,20(2):21-23. 被引量:1

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