Acta Optica Sinica, Volume. 37, Issue 10, 1011001(2017)

Mixed Manifold Spectral Clustering Adaptive Segmentation Method for Laser Point Cloud

Shuai Wang1、*, Huayan Sun2, Huichao Guo2, and Lin Du1
Author Affiliations
  • 1 Department of Postgraduate, Academy of Equipment, Beijing 101416, China
  • 2 Department of Photoelectricity & Equipment, Academy of Equipment, Beijing 101416, China;
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    Figures & Tables(7)
    Segmentation results of simulated point sets. (a) Spirals made by two curves; (b) crossed lines and plane
    Segmentations of point clouds based on target geometry. (a) Rabbit; (b) Horse; (c) Armadillo
    Relationship between consistency of segmentation and M
    Relationship between time consuming and M
    Relationship between consistency of segmentation and value of kNN
    Segmentation results of point clouds with noises by different segmentation algorithms. (a) Point cloud with noise; (b) k-means algorithm; (c) local angular distance spectral clustering algorithm; (d) proposed algorithm
    Segmentation results of point cloud of satellite model. (a) Gray image; (b) side view of slice three-dimensional imaging; (c) front view of segmentation by the proposed algorithm; (d) side view of segmentation by the proposed algorithm
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    Shuai Wang, Huayan Sun, Huichao Guo, Lin Du. Mixed Manifold Spectral Clustering Adaptive Segmentation Method for Laser Point Cloud[J]. Acta Optica Sinica, 2017, 37(10): 1011001

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    Paper Information

    Category: Imaging Systems

    Received: May. 5, 2017

    Accepted: --

    Published Online: Sep. 7, 2018

    The Author Email:

    DOI:10.3788/AOS201737.1011001

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