Optics and Precision Engineering, Volume. 30, Issue 22, 2962(2022)

3D laser point cloud skeleton extraction via balance of local correlation points

Minquan ZHOU, Chunhui LI, Liqing WANG, Yuhe ZHANG, and Guohua GENG*
Author Affiliations
  • College of Information Science and Technology, Northwest University, Xi'an710127, China
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    Figures & Tables(11)
    Pipeline of proposed method
    Schematic diagram of normal vector ambiguity
    Figure (a) shows that when the point (marked red) to be judged is outside the model, the intersection of the yellow ray and the model (marked green) has two even numbers. The point (marked red) to be judged in the figure (b) is inside the model, and there is an odd number at the intersection of the yellow ray and the model (marked green)
    (a) shows the method of obtaining the plane perpendicular to qin, and pi+1 is the nearest sampling point from pi, in (b), the skeleton point qi is in an unbalanced position, and in (c), the skeleton point qi is in an balanced position
    Difference between R and RL. (a) is R, and (b) is RLobtained through breadth first search according to R
    Curve skeleton of some models (right) and the display of the original model (left) extracted by this algorithm
    Effect comparison of curve skeleton extracted by various methods
    Effect comparison of curve skeleton extracted by various methods when inputting the model with noise
    Action transformation of lidar point cloud based on the guidance of curve skeleton
    • Table 1. Statistics of the number of skeleton points, topological connections, junction points and topological connection errors of several methods

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      Table 1. Statistics of the number of skeleton points, topological connections, junction points and topological connection errors of several methods

      MethodModel
      DogHorseHuman-1
      NoneNoiseNoneNoiseNoneNoise
      L1-MedialNumber of skeleton points434853666361
      Number of topologies414552646259
      Number of junction points201222
      Number of topology errors444101
      MdCSNumber of skeleton points412414202324
      Number of topologies432416192424
      Number of junction points1216254
      Number of topology errors614121
      Point2SkeletonNumber of skeleton points100100100100100100
      Number of topologies192114142114
      Number of junction points117531
      Number of topology errors1317871512
      OursNumber of skeleton points474742424846
      Number of topologies464641414745
      Number of junction points222212
      Number of topology errors000010
    • Table 2. Running time of different algorithms

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      Table 2. Running time of different algorithms

      Data set#PointsL1-MedialMdCSP2SOurs
      Horse8 07711.520125.1587.7290.764
      Dog9 00915.491213.0767.6080.830
      Indore12 12819.452360.9128.3151.029
      Human-128 51872.3218.2353.328
      Human-233 04186.1108.4694.356
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    Minquan ZHOU, Chunhui LI, Liqing WANG, Yuhe ZHANG, Guohua GENG. 3D laser point cloud skeleton extraction via balance of local correlation points[J]. Optics and Precision Engineering, 2022, 30(22): 2962

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    Paper Information

    Category: Information Sciences

    Received: Apr. 26, 2022

    Accepted: --

    Published Online: Nov. 28, 2022

    The Author Email: GENG Guohua (ghgeng@nwu.edu.cn)

    DOI:10.37188/OPE.20223022.2962

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