Literature DB >> 23929849

Cylinder detection in large-scale point cloud of pipeline plant.

Yong-Jin Liu1, Jun-Bin Zhang, Ji-Chun Hou, Ji-Cheng Ren, Wei-Qing Tang.   

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 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.

Year:  2013        PMID: 23929849     DOI: 10.1109/TVCG.2013.74

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  3 in total

1.  Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites.

Authors:  Reza Maalek; Derek D Lichti; Janaka Y Ruwanpura
Journal:  Sensors (Basel)       Date:  2018-03-08       Impact factor: 3.576

2.  Automatic Detection and Modeling of Underground Pipes Using a Portable 3D LiDAR System.

Authors:  Ahmad K Aijazi; Laurent Malaterre; Laurent Trassoudaine; Thierry Chateau; Paul Checchin
Journal:  Sensors (Basel)       Date:  2019-12-04       Impact factor: 3.576

3.  Multiple Cylinder Extraction from Organized Point Clouds.

Authors:  Saed Moradi; Denis Laurendeau; Clement Gosselin
Journal:  Sensors (Basel)       Date:  2021-11-17       Impact factor: 3.576

  3 in total

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