Journals Articles Conferences News About CLP
Submit a paper Email Alert
Search
Search
Articles
Journals
News
Advanced Search
Top Searches
2D MaterialsTransformation opticsQuantum PhotonicsSmall lasersSemiconductor UV PhotonicsSupersymmetric microring laser arrays

Chinese Journal of Lasers, Volume. 48, Issue 16, 1604002(2021)

New Method for Plane Segmentation of Indoor Scene Point Cloud

Qiqi Li1,2, Xianghong Hua1,2、*, Bufan Zhao1,2,3, Wuyong Tao1,2, and Cheng Li1,2
Author Affiliations
  • 1School of Surveying and Mapping, Wuhan University, Wuhan, Hubei 430079, China
  • 2Disaster Monitoring and Prevention Research Center of Wuhan University, Wuhan, Hubei 430079, China
  • 3Key Laboratory for Digital Land and Resources of Jiangxi Province, East China University of Technology, Nanchang, Jiangxi 330013, China
    • show less
    AbstractGet PDF(in Chinese)
    Figures&Tables (13)
    Equations (0)
    References (25)
    Cited By (6)
    Tools
    Paper Information
    Topics
    Figures & Tables(13)
    Processing flow of proposed method

    Fig. 1. Processing flow of proposed method

    Download full size
    Projection length model of point cloud

    Fig. 2. Projection length model of point cloud

    Download full size
    Three sets of data used in experiment. (a) data 1; (b) data 2; (c) data 3

    Fig. 3. Three sets of data used in experiment. (a) data 1; (b) data 2; (c) data 3

    Download full size
    Number of stratified point clouds

    Fig. 4. Number of stratified point clouds

    Download full size
    Normal Gaussian map and point cloud before and after normal constraint. (a) Gaussian ball; (b) partial zoom; (c) constrained normal vector; (d) point cloud at maximum layer 1; (e) point cloud at maximum layer 2; (f) constrained point cloud

    Fig. 5. Normal Gaussian map and point cloud before and after normal constraint. (a) Gaussian ball; (b) partial zoom; (c) constrained normal vector; (d) point cloud at maximum layer 1; (e) point cloud at maximum layer 2; (f) constrained point cloud

    Download full size
    Preliminary segmentation results of data 1. (a) Partitioned plane point clouds; (b) floor and ceiling plans; (c) residual point clouds

    Fig. 6. Preliminary segmentation results of data 1. (a) Partitioned plane point clouds; (b) floor and ceiling plans; (c) residual point clouds

    Download full size
    Plane segmentation results of data 1 after model optimization

    Fig. 7. Plane segmentation results of data 1 after model optimization

    Download full size
    Plane segmentation results of point clouds in data 2 and data 3. data 2 plane point cloud, (a) segmentation results, (b) residual point cloud; data 3 plane point cloud, (c) segmentation results, (d) residual point cloud

    Fig. 8. Plane segmentation results of point clouds in data 2 and data 3. data 2 plane point cloud, (a) segmentation results, (b) residual point cloud; data 3 plane point cloud, (c) segmentation results, (d) residual point cloud

    Download full size

    • Table 1. Parameters of planes in point cloud of data 1 scene

      View table

      Table 1. Parameters of planes in point cloud of data 1 scene

      PlaneABD
      Plane 1213.27450.03051971.6564
      Plane 2-2.5988×10-51.7823×10-5-0.0034
      Plane 326.3625-26.9836469.1850
      Plane 4-2.7181×10-61.0147×10-53.3648
      Plane 5-82.5261-0.3624-1122.2972
      Plane 6-498.51250.0325-5334.4432
      Plane 7-281.2597-281.1161-2618.1471
      Plane 80.00161.1324×10-41.1738
      Plane 90.0273-148.163977.4453
      Plane 10-0.2417-93.3212197.1178
      Plane 1125.7364-25.7179454.0566

    • Table 2. Comparison between peak interval of projection length ρ of plane model and projection length of point cloud

      View table

      Table 2. Comparison between peak interval of projection length ρ of plane model and projection length of point cloud

      ParameterPlane 1Plane 2Plane 3Plane 4Plane 5Plane 6Plane 7Plane 8Plane 9Plane 10
      ρ9.2440.00312.4333.36513.59810.7016.5841.1740.5232.112
      Peak interval[9.225,9.275][0.025,0.075][12.425,12.475][3.325,3.375][13.625,13.675][10.675,10.725][6.575,6.625][1.125,1.175][0.475,0.525][2.125,2.175]

    • Table 3. Segmentation precision of plane point cloud

      View table

      Table 3. Segmentation precision of plane point cloud

      ObjectModeldistance /mAverage distance /mMeasured distance /mDistanceerror /mmRelative accuracy /%
      Ceiling-desktop Desktop-ceiling2.25982.25922.25952.25722.399.89
      Floor-ceilingCeiling-floor3.02253.02213.02233.01804.399.86
      Front wall-back wallBack wall-front wall5.97305.97445.97375.97491.299.97
      Left wall-right wallRight wall-left wall7.75777.75447.75617.75322.999.96

    • Table 4. Deflection angle of planes

      View table

      Table 4. Deflection angle of planes

      ObjectCeilingFloorDesktopFront wallBack wallLeft wallRight wall
      Deflection angle/(°)0.0770.0560.1470.0280.1700.1350.103

    • Table 5. Segmentation time-consuming of plane point clouds

      View table

      Table 5. Segmentation time-consuming of plane point clouds

      DataNumber of pointsProposed method /sMLESAC method/sImproved 3D-HT method /s
      11145824.76015.68710.291
      240928616.72460.38531.516
      3167243467.997208.213140.930
    Tools

    Get Citation

    Copy Citation Text

    Qiqi Li, Xianghong Hua, Bufan Zhao, Wuyong Tao, Cheng Li. New Method for Plane Segmentation of Indoor Scene Point Cloud[J]. Chinese Journal of Lasers, 2021, 48(16): 1604002

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Set citation alerts for article
    Save article for my favorites
    Paper Information

    Category: measurement and metrology

    Received: Dec. 17, 2020

    Accepted: Feb. 25, 2021

    Published Online: Aug. 6, 2021

    The Author Email: Xianghong Hua (xhhua@sgg.whu.edu.cn)

    DOI:10.3788/CJL202148.1604002

    Topics

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