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Laser & Optoelectronics Progress, Volume. 58, Issue 24, 2410013(2021)

Point Cloud Semantic Segmentation Based on KNN-PointNet

Xiaowen Yang*, Aibing Wang, Xie Han, Rong Zhao, and Yuxin Jin
Author Affiliations
  • School of Data Science and Technology, North University of China, Taiyuan, Shanxi 030051, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (9)
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    References (19)
    Cited By (6)
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    Figures & Tables(9)
    Classification effect of points to be measured in local neighborhood

    Fig. 1. Classification effect of points to be measured in local neighborhood

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    local feature extraction process

    Fig. 2. local feature extraction process

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    KNN-PointNet framework

    Fig. 3. KNN-PointNet framework

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    Segmentation results of improved KNN algorithm and KNN algorithm

    Fig. 4. Segmentation results of improved KNN algorithm and KNN algorithm

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    Visualization results of scene segmentation under different algorithms. (a) Original point cloud; (b) true segmentation; (c) PointNet; (d) PointNet++

    Fig. 5. Visualization results of scene segmentation under different algorithms. (a) Original point cloud; (b) true segmentation; (c) PointNet; (d) PointNet++

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    Visualization results of proposed algorithm

    Fig. 6. Visualization results of proposed algorithm

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    Segmentation results under different k and r values

    Fig. 7. Segmentation results under different k and r values

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    • Table 1. Performance comparison between improved KNN algorithm and other algorithms unit: %

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      Table 1. Performance comparison between improved KNN algorithm and other algorithms unit: %

      AlgorithmmAccmIoUoAcc
      PointNet57.841.182.3
      PointNet++--52.4--
      G+RCU--45.1--
      3P-RNN--53.485.7
      Engelmann--52.284.2
      TangentConv--52.882.5
      ASIS--51.1--
      Proposed algorithm81.556.385.8

    • Table 2. IoU results of 13 semantic categories on S3DIS dataset for different networks unit: %

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      Table 2. IoU results of 13 semantic categories on S3DIS dataset for different networks unit: %

      TypePointNetPointNet++Proposed network
      Ceiling84.090.590.2
      Floor80.790.091.2
      Wall55.365.274.3
      Beam42.463.370.1
      Pillar26.340.245.2
      Window40.550.356.5
      Door38.642.343.2
      Chair55.068.470.5
      Table30.136.948.3
      Sofa9.632.226.4
      Bookcase27.236.546.3
      Board19.434.238.1
      Clutter25.231.231.6
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    Xiaowen Yang, Aibing Wang, Xie Han, Rong Zhao, Yuxin Jin. Point Cloud Semantic Segmentation Based on KNN-PointNet[J]. Laser & Optoelectronics Progress, 2021, 58(24): 2410013

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    Paper Information

    Category: Image Processing

    Received: May. 26, 2021

    Accepted: Jul. 20, 2021

    Published Online: Nov. 29, 2021

    The Author Email: Xiaowen Yang (wenyang1314@nuc.edu.cn)

    DOI:10.3788/LOP202158.2410013

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology