Laser Technology, Volume. 47, Issue 1, 59(2023)

Classification of terrestrial point cloud considering point density and unknown angular resolution

ZHANG Xinyi, CHEN Maolin, LIU Xiangjiang, JI Cuicui, and ZHAO Lidu
Author Affiliations
  • [in Chinese]
  • show less
    References(24)

    [1] [1] LIN Ch D, XIE L Y, HAN J, et al. Recognition of the number of corn plants in farmland based on laser point cloud[J]. Laser Technology,2022,46(2):220-225(in Chinese).

    [3] [3] HUANG F, LI W T, HOU Y F, et al. Tuneldata processing and deformation analysis study based on laser point cloud[J]. Science of Surveying and Mapping, 2019, 44(5):132-137(in Chinese).

    [4] [4] LAI X D, YANG J R, LI Y X, et al. A building extraction approach based on the fusion of LiDAR point cloud and elevation map texture features[J]. Remote Sensing, 2019, 11(14): 1636.

    [5] [5] PAN Y, DONG Y Q, WANG D L, et al. Three-dimensional reconstruction of structural surface model of heritage bridges using UAV-based photogrammetric point clouds[J]. Remote Sensing, 2019,11(10): 1204.

    [6] [6] HU H Y, HUI Zh Y, LI N. Airborne LiDAR point cloud classification based on multiple-entity eigenvetor fusion[J]. Chinese Journal of Lasers, 2020,47(8): 0810002(in Chinese).

    [7] [7] XUE D D, CHENG Y L, SHI X S, et al. Point clouds classification algorithm based on cloth filtering algorithm improved random forest[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221017(in Chinese).

    [9] [9] WEINMANN M, JUTZI B, HINZ S, et al. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 105: 286-304.

    [10] [10] CHEN M L, LIU X J, ZHANG X Y, et al. Building extraction from terrestrial laser scanning data with density of projected points on polar grid and adaptive threshold[J]. Remote Sensing, 2021, 13(21): 4392.

    [11] [11] CHE E, OLSEN M J. Fast ground filtering for TLS data via scanline density analysis[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 129: 226-240.

    [12] [12] SHI W Zh, LI B J, LI Q Q. A method for segmentation of range image captured by vehicle-borne laser scanning based on the density of projected points[J]. Acta Geodaetica et Cartographica Sinica, 2005, 34(2): 95-100(in Chinese).

    [13] [13] SUN H, WANG G X, LIN H, et al. Retrieval and accuracy assessment of tree and stand parameters for Chinese fir plantation using terrestrial laser scanning[J]. IEEE Geoscience and Remote Sensing Letters, 2015, 12(9): 1993-1997.

    [14] [14] CHENG X L, CHENG X J, LI Q, et al. Automatic registration of terrestrial and airborne point clouds using building outline features[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11(2): 628-638.

    [15] [15] LIU K Q, WANG W G, THARMARASA R, et al. Dynamic vehicle detection with sparse point clouds based on PE-CPD[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 20(5): 1964-1977.

    [16] [16] DEMANTK J, MALLET C, DAVID N, et al. Dimensionality based scale selection in 3D lidar point clouds[J]. ISPRS-International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, 2011, 38(5):97-102.

    [17] [17] LI J, YAO L. Ground laser point cloud semantic segmentation based on multi-feature deep learning [J]. Science of Surveying and Mapping, 2021, 46(3): 133-139(in Chinese).

    [18] [18] ATIK M E, DURAN Z, SEKER D Z. Machine learning-based supervised classification of point clouds using multiscale geometric features[J]. ISPRS International Journal of Geo-Information, 2021, 10(3): 187.

    [19] [19] CHEN M L, WAN Y C, WANG M W, et al. Automatic stem detection in terrestrial laser scanning data with distance-adaptive search radius[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(5): 2968-2979.

    [20] [20] CHEN M L, PAN J P, XU J Zh. Classification of terrestrial laser scanning data with density-adaptive geometric features[J]. IEEE Geoscience and Remote Sensing Letters, 2018, 15(11): 1795-1799.

    [21] [21] HACKEL T, SAVINOV N, LADICKY L, et al. Semantic3d. net: A new large-scale point cloud classification benchmark[J]. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, IV-1-W1:91-98.

    [22] [22] DONG Zh, LIANG F X, YANG B Sh, et al. Registration of large-scale terrestrial laser scanner point clouds: A review and benchmark[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020,163: 327-342.

    [23] [23] ZHANG W M, QI J B, WAN P, et al. An easy-to-use airborne LiDAR data filtering method based on cloth simulation[J]. Remote Sensing, 2016, 8(6): 501.

    [24] [24] ZHANG Zh G, SUN L C, WANG P. Research on pedestrian detection method based on laser scanning[J]. Computer Science, 2016, 43(7): 328-331(in Chinese).

    CLP Journals

    [1] AN Aobo, CHEN Maolin, ZHAO Lidu, MA Chenglin, LIU Xiangjiang. Density adaptive plane segmentation from long-range point cloud[J]. Laser Technology, 2023, 47(5): 606

    Tools

    Get Citation

    Copy Citation Text

    ZHANG Xinyi, CHEN Maolin, LIU Xiangjiang, JI Cuicui, ZHAO Lidu. Classification of terrestrial point cloud considering point density and unknown angular resolution[J]. Laser Technology, 2023, 47(1): 59

    Download Citation

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

    Category:

    Received: Nov. 12, 2021

    Accepted: --

    Published Online: Apr. 12, 2023

    The Author Email:

    DOI:10.7510/jgjs.issn.1001-3806.2023.01.009

    Topics