Optics and Precision Engineering, Volume. 31, Issue 17, 2564(2023)

Ground point cloud segmentation based on local threshold adaptive method

Peixiang ZHANG1...2, Qi WANG1,2, Renjing GAO1,2,*, Yang XIA1 and Zhenzhong WAN3 |Show fewer author(s)
Author Affiliations
  • 1State Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Automotive Engineering, Dalian University of Technology, Dalian6024, China
  • 2Ningbo Institute of Dalian University of Technology, Ningbo315000, China
  • 3BYD Auto Industry Company Limited, Shenzhen518118, China
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    Figures & Tables(12)
    Schematic diagram of point cloud adaptive threshold ground segmentation algorithm model
    Polar division of point cloud data
    Vehicle driving road map
    Effect of distribution of regional bi points on dmax
    Point cloud distribution hypothesis map
    Flowchart of seed point set update
    Flowchart of ground point segmentation
    Segmentation of semantic KITTI road information
    Binary division result of semantic KITTI dataset
    Segmentation result of proposed algorithm
    Point cloud segmentation results of different algorithms
    • Table 1. Comparison of segmentation results of Semantic KITTI binary dataset

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      Table 1. Comparison of segmentation results of Semantic KITTI binary dataset

      分割算法精确率召回率平均运行时间/ms
      固定阈值0.902 5070.868 95723.2
      文献[80.913 6070.839 65117.5
      文献[170.891 9610.854 25719.1
      本文算法0.932 7510.880 66126.4
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    Peixiang ZHANG, Qi WANG, Renjing GAO, Yang XIA, Zhenzhong WAN. Ground point cloud segmentation based on local threshold adaptive method[J]. Optics and Precision Engineering, 2023, 31(17): 2564

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    Paper Information

    Category: Information Sciences

    Received: Dec. 15, 2022

    Accepted: --

    Published Online: Oct. 9, 2023

    The Author Email: GAO Renjing (renjing@dlut.edu.cn)

    DOI:10.37188/OPE.20233117.2564

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