Chinese Journal of Lasers, Volume. 45, Issue 11, 1104004(2018)
An Automatic Segmentation Algorithm for Dense Pipeline Point Cloud Data
Fig. 5. Schematic of plane point cloud filtering based on normal vector constraints
Fig. 8. Virtual scenes in experiment 1. (a) Top view; (b) front view; (c) left view; (d) southeast side view
Fig. 11. Segmentation results of pipeline data in experiment 1. (a) Southeast side view; (b) top view
Fig. 14. Sketch of registered point cloud in experiment 2. (a) Left view; (b) southeast side view
Fig. 15. Sketch after removal of large planes in experiment 2. (a) Top view; (b) southeast side view
Fig. 16. Segmentation result of pipeline data in experiment 2. (a) Top view; (b) front view; (c) southeast side view; (d) southwest side view
Fig. 17. Segmentation sketch of pipeline data in experiment 1, where segmented pipeline data are indicated in white domain. (a) Top view; (b) southwest side view
Fig. 18. Segmentation sketch of pipeline data in experiment 2, where segmented pipeline data are indicated in white domain. (a) Top view; (b) southeast side view
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Huang Kai, Cheng Xiaojun, Jia Dongfeng, Hu Danhua, Hu Minjie. An Automatic Segmentation Algorithm for Dense Pipeline Point Cloud Data[J]. Chinese Journal of Lasers, 2018, 45(11): 1104004
Category: Measurement and metrology
Received: Apr. 18, 2018
Accepted: --
Published Online: Nov. 15, 2018
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