Cylinder detection in large-scale point cloud of pipeline plant
Published in IEEE Transactions on Visualization and Computer Graphics, 2013
Abstract: 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 $\mathbb{R}^{3}$ into a set of simple circle detection problems in $\mathbb{R}^{2}$. Experiments with industrial applications are presented, which demonstrate the efficiency of the proposed structure detection method.
Recommended citation: Yong-Jin Liu, Jun-Bin Zhang, Ji-Chun Hou, Ji-Cheng Ren, Wei-Qing Tang (2013) Cylinder detection in large-scale point cloud of pipeline plant. IEEE Transactions on Visualization and Computer Graphics, Vol. 19, No. 10, pp. 1700-1707, 2013.