Laser & Optoelectronics Progress, Volume. 60, Issue 14, 1428009(2023)

Rapid Removal Algorithm of Road Surface Point Cloud Based on LP-RANSAC Algorithm

Yong Zuo*, Yang Ren**, Zhihua Du, Jifang Qiu, Yan Li, Hongxiang Guo, Xiaobin Hong, and Jian Wu
Author Affiliations
  • College of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
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    References(16)

    [1] Liu B, Yu Y, Jiang S. Review of advances in LiDAR detection and 3D imaging[J]. Opto-Electronic Engineering, 46, 190167(2019).

    [2] Li W L, Long S L. Application of unmanned lidar in topographic mapping of mountainous areas[J]. Technology Innovation and Application, 145-147(2020).

    [3] Tian X B, Zhang Y L, Wu J W et al. Research and practice of site surveying by UAV LiDAR and BIM planning design[J]. Journal of Graphics, 39, 339-345(2018).

    [4] Si D G. The application of airborne light detection and ranging in expressway survey and design[D](2018).

    [5] Gao R Q, Zhang X F, Sun Q et al. Road pavement monitoring and roughness assessment based on UAV LiDAR data[J]. Journal of Basic Science and Engineering, 26, 681-696(2018).

    [6] Huang S Y, Liu L M, Dong J et al. Review of ground filtering algorithms for vehicle LiDAR scans point cloud data[J]. Opto-Electronic Engineering, 47, 190688(2020).

    [7] Asvadi A, Premebida C, Peixoto P et al. 3D Lidar-based static and moving obstacle detection in driving environments: an approach based on voxels and multi-region ground planes[J]. Robotics and Autonomous Systems, 83, 299-311(2016).

    [8] Li L, Yang F, Zhu H H et al. An improved RANSAC for 3D point cloud plane segmentation based on normal distribution transformation cells[J]. Remote Sensing, 9, 433(2017).

    [9] Wu Y, Li G Q, Xian C H et al. Extracting POP: Pairwise orthogonal planes from point cloud using RANSAC[J]. Computers & Graphics, 94, 43-51(2021).

    [10] Guan J Z, Pan W Q. Ground point cloud extraction algorithm based on multi-region RANSAC[J]. Electronic Technology & Software Engineering, 176-177(2020).

    [11] Ebrahimi A, Czarnuch S. Automatic super-surface removal in complex 3D indoor environments using iterative region-based RANSAC[J]. Sensors, 21, 3724(2021).

    [12] Charles R Q, Hao S, Mo K C et al. PointNet: deep learning on point sets for 3D classification and segmentation[C], 77-85(2017).

    [13] Hua B S, Tran M K, Yeung S K. Pointwise convolutional neural networks[C], 984-993(2018).

    [14] Li J, Yao L. Ground laser point cloud semantic segmentation based on multi-feature deep learning[J]. Science of Surveying and Mapping, 46, 133-139, 162(2021).

    [15] Velas M, Spanel M, Hradis M et al. CNN for very fast ground segmentation in velodyne LiDAR data[C], 97-103(2018).

    [16] Fischler M A, Bolles R C. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography[J]. Communications of the ACM, 24, 381-395(1981).

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    Yong Zuo, Yang Ren, Zhihua Du, Jifang Qiu, Yan Li, Hongxiang Guo, Xiaobin Hong, Jian Wu. Rapid Removal Algorithm of Road Surface Point Cloud Based on LP-RANSAC Algorithm[J]. Laser & Optoelectronics Progress, 2023, 60(14): 1428009

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Feb. 11, 2022

    Accepted: Sep. 5, 2022

    Published Online: Jul. 17, 2023

    The Author Email: Zuo Yong (yong_zuo@bupt.edu.cn), Ren Yang (ry1224@163.com)

    DOI:10.3788/LOP220707

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