Laser & Optoelectronics Progress, Volume. 59, Issue 18, 1811006(2022)

Hierarchical Simplification Algorithm for Scattered Point Clouds

Fuqun Zhao* and Hui Tang
Author Affiliations
  • School of Information, Xi’an University of Finance and Economics, Xi’an 710100, Shaanxi , China
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    Figures & Tables(10)
    Original common point cloud model. (a) Bunny; (b) Horse
    Simplified results of Bunny model. (a) Random sampling algorithm; (b) uniform grid algorithm; (c) normal vector anglealgorithm; (d) algorithm in reference [7]; (e) algorithm in reference [16]; (f) proposed algorithm
    Simplified results of Horse model. (a) Random sampling algorithm; (b) uniform grid algorithm; (c) normal vector anglealgorithm; (d) algorithm in reference [7]; (e) algorithm in reference [16]; (f) proposed algorithm
    Original texture model of cultural relic fragment.(a) Fragment 1; (b) fragment 2; (c) fragment 3
    Point cloud model of cultural relic fragment. (a) Fragment 1; (b) fragment 2; (c) fragment 3
    Simplified results of fragment 1. (a) Random sampling algorithm; (b) uniform grid algorithm; (c) normal vector anglealgorithm; (d) algorithm in reference [7]; (e) algorithm in reference [16]; (f) proposed algorithm
    Simplified results of fragment 2. (a) Random sampling algorithm; (b) uniform grid algorithm; (c) normal vector anglealgorithm; (d) algorithm in reference [7]; (e) algorithm in reference [16]; (f) proposed algorithm
    Simplified results of fragment 3. (a) Random sampling algorithm; (b) uniform grid algorithm; (c) normal vector anglealgorithm; (d) algorithm in reference [7]; (e) algorithm in reference [16]; (f) proposed algorithm
    • Table 1. Simplified parameters of common point cloud model by six algorithms

      View table

      Table 1. Simplified parameters of common point cloud model by six algorithms

      Point cloud modelPoint numberAlgorithmSimplification rateFeature pointsMaximum errorAverage errorSimplify time /s
      Bunny35947Random sampling0.324460.10270.041330.24
      Uniform grid0.554790.10190.040932.74
      Normal vector angle0.675010.08240.035235.19
      Reference[70.755770.07060.033927.55
      Reference[160.776460.06880.031429.42
      Proposed algorithm0.806960. 05810.028120.46
      Horse48485Random sampling0.304880.11310.053331.70
      Uniform grid0.605140.11220.051034.19
      Normal vector angle0.655730.09300.046736.33
      Reference[70.705980.08020.042928.72
      Reference[160.806440.07850.040830.99
      Proposed algorithm0.836900. 06220.038621.91
    • Table 2. Simplified parameters of cultural relic fragment point cloud model by six algorithms

      View table

      Table 2. Simplified parameters of cultural relic fragment point cloud model by six algorithms

      Point cloud modelPoint numberAlgorithmSimplification rateFeature pointsMaximum errorAverage errorSimplify time /s
      Fragment 16421Random sampling0.311220.13830.047930.13
      Uniform grid0.321940.13720.046732.19
      Normal vector angle0.332010.12880.038134.55
      Reference[70.352680.12680.035427.09
      Reference[160.673050.12440.031630.94
      Proposed algorithm0.763220.12060.029920.01
      Fragment 210348Random sampling0.332410.13770.046832.33
      Uniform grid0.332890.13670.045834.40
      Normal vector angle0.343030.12680.035536.69
      Reference[70.373520.12370.032329.30
      Reference[160.614030.12190.030933.09
      Proposed algorithm0.734420.11840.028522.33
      Fragment 3115472Random sampling0.304600.14970.058935.62
      Uniform grid0.324880.14900.058337.58
      Normal vector angle0.315410.14080.048539.92
      Reference[70.336290.13140.044932.68
      Reference[160.617010.12650.041836.02
      Proposed algorithm0.697700.12460.038625.49
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    Fuqun Zhao, Hui Tang. Hierarchical Simplification Algorithm for Scattered Point Clouds[J]. Laser & Optoelectronics Progress, 2022, 59(18): 1811006

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    Paper Information

    Category: Imaging Systems

    Received: Jul. 14, 2021

    Accepted: Sep. 24, 2021

    Published Online: Aug. 30, 2022

    The Author Email: Zhao Fuqun (fuqunzhao@126.com)

    DOI:10.3788/LOP202259.1811006

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