Cylinder detection in large-scale point cloud of pipeline plant

Yong-Jin Liu Tsinghua University Jun-Bin Zhang Tsinghua University Ji-Chun Hou Tsinghua University Ji-Cheng Ren Beijing Zhongke Fulong Computer Technology Co. Wei-Qing Tang Beijing Zhongke Fulong Computer Technology Co.

Geometric Modeling and Processing mathscidoc:1608.16003

IEEE Transactions on Visualization and Computer Graphics, 19, (10), 1700, 2013.10
The huge number of points scanned from pipeline plants make the plant reconstruction very difficult. Traditional cylinder detection methods cannot be applied directly due to the high computational complexity. In this paper, we explore the structural characteristics of point cloud in pipeline plants and define a structure feature. Based on the structure feature, we propose a hierarchical structure detection and decomposition method that reduces the difficult pipeline-plant reconstruction problem in IR3 into a set of simple circle detection problems in IR2. Experiments with industrial applications are presented, which demonstrate the efficiency of the proposed structure detection method.
3D reconstruction, point cloud, structure analysis
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@inproceedings{yong-jin2013cylinder,
  title={Cylinder detection in large-scale point cloud of pipeline plant},
  author={Yong-Jin Liu, Jun-Bin Zhang, Ji-Chun Hou, Ji-Cheng Ren, and Wei-Qing Tang},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20160819154232482910268},
  booktitle={IEEE Transactions on Visualization and Computer Graphics},
  volume={19},
  number={10},
  pages={1700},
  year={2013},
}
Yong-Jin Liu, Jun-Bin Zhang, Ji-Chun Hou, Ji-Cheng Ren, and Wei-Qing Tang. Cylinder detection in large-scale point cloud of pipeline plant. 2013. Vol. 19. In IEEE Transactions on Visualization and Computer Graphics. pp.1700. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20160819154232482910268.
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