• Optics and Precision Engineering
  • Vol. 32, Issue 12, 1941 (2024)
Xijiang CHEN1,2,3, Xi SUN2,*, Bufan ZHAO2, Qing AN1, and Xianquan HAN4
Author Affiliations
  • 1School of Artificial Intelligence, Wuchang University of Technology, Wuhan430223,China
  • 2School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan430070,China
  • 3Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang001,China
  • 4Changjiang River Scientific Research Institute of Changjiang Water Resources Commission, Wuhan30019,China
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    DOI: 10.37188/OPE.20243212.1941 Cite this Article
    Xijiang CHEN, Xi SUN, Bufan ZHAO, Qing AN, Xianquan HAN. Part segmentation method of point cloud considering optimal allocation and optimal mask[J]. Optics and Precision Engineering, 2024, 32(12): 1941 Copy Citation Text show less
    Flow chart of the method in this article
    Fig. 1. Flow chart of the method in this article
    Schematic diagram of the optimal transport
    Fig. 2. Schematic diagram of the optimal transport
    Schematic diagram of the method presented in this paper
    Fig. 3. Schematic diagram of the method presented in this paper
    Significance visualization plot, the significance points are marked in red
    Fig. 4. Significance visualization plot, the significance points are marked in red
    Knn and ball query visualization compare Fig
    Fig. 5. Knn and ball query visualization compare Fig
    Distribution map of the sampling number of each class in the ShapeNet data set
    Fig. 6. Distribution map of the sampling number of each class in the ShapeNet data set
    Airplane visualization
    Fig. 7. Airplane visualization
    Table visualization
    Fig. 8. Table visualization
    Cap visualization
    Fig. 9. Cap visualization
    Earphone visualization
    Fig. 10. Earphone visualization
    Knife visualization
    Fig. 11. Knife visualization
    Computer visualization
    Fig. 12. Computer visualization
    Pistol visualization
    Fig. 13. Pistol visualization
    Airplane visualization
    Fig. 14. Airplane visualization
    Proportion of enhanced samples
    Fig. 15. Proportion of enhanced samples
    方法mIoUAir-planeBagCapCarChairEar-phoneGuitarKnifeLampLaptopMotor-bikeMugPistolRocketSkate-boardTable
    #shapes/269076558983758697873921547451202184283661525271
    PointNet83.783.478.782.574.989.673.091.585.980.895.365.293.081.257.972.880.6
    PointNet+Ours85.183.882.984.275.590.270.891.586.382.395.266.193.981.063.171.181.2
    PointNet++85.182.479.087.777.390.871.891.085.983.795.371.694.181.358.776.482.6
    PointNet+++Ours86.382.683.288.577.991.472.591.086.384.295.372.494.781.164.874.783.2
    DGCNN85.184.283.784.477.190.978.591.587.382.996.067.893.382.659.775.582.0
    DGCNN+Ours86.084.684.185.677.891.379.091.387.783.495.768.593.582.164.573.282.8
    Table 1. Part segmentation results on the ShapeNet dataset
    混合方式mIoU/%
    PointCutMix85.5
    xαxβ82.3
    xαxβ85.0
    xαxβ85.2
    xαxβ86.1
    Table 2. Comparison of the different mixing methods
    基准点的显著性掩码最佳掩码mIoU/%
    85.1
    85.5
    85.2
    85.4
    85.7
    86.3
    Table 3. Results of the ablation experiments
    抖动旋转随机丢弃点本文方法mIoU/%
    86.3(a)
    85.3(b)
    85.7
    85.3(b)
    86.6
    85.4(b)
    85.9
    85.9
    Table 4. Results combined with traditional methods
    Xijiang CHEN, Xi SUN, Bufan ZHAO, Qing AN, Xianquan HAN. Part segmentation method of point cloud considering optimal allocation and optimal mask[J]. Optics and Precision Engineering, 2024, 32(12): 1941
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