• Opto-Electronic Engineering
  • Vol. 47, Issue 12, 190688 (2020)
Huang Siyuan1, Liu Limin1、*, Dong Jian1, and Fu Xiongjun2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • show less
    DOI: 10.12086/oee.2020.190688 Cite this Article
    Huang Siyuan, Liu Limin, Dong Jian, Fu Xiongjun. Review of ground filtering algorithms for vehicle LiDAR scans point cloud data[J]. Opto-Electronic Engineering, 2020, 47(12): 190688 Copy Citation Text show less
    References

    [2] Habermann D, Hata A, Wolf D, et al. 3D point clouds segmenta-tion for autonomous ground vehicle[C]//2013 III Brazilian Sym-posium on Computing Systems Engineering, Niteroi, Brazil, 2013: 143–148.

    [7] Douillard B, Underwood J, Vlaskine V, et al. A pipeline for the segmentation and classification of 3D point clouds[C]//The 12th International Symposium on Experimental Robotics (ISER), Ber-lin, Heidelberg, 2014: 585–600.

    [8] Zhu Z, Liu J L. Graph-based ground segmentation of 3D LIDAR in rough area[C]//2014 IEEE International Conference on Tech-nologies for Practical Robot Applications, Woburn, MA, USA, 2014.

    [9] Thrun S, Montemerlo M, Dahlkamp H, et al. Stanley: the robot that won the DARPA grand challenge[J]. Journal of Field Ro-botics, 2006, 23(9): 661–692.

    [10] Douillard B, Underwood J, Melkumyan N, et al. Hybrid elevation maps: 3D surface models for segmentation[C]//2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, China, 2010: 1532–1538.

    [11] Kammel S, Pitzer B. Lidar-based lane marker detection and mapping[C]//2008 IEEE Intelligent Vehicles Symposium, Eind-hoven, Netherlands, 2008: 1137–1142.

    [12] Guo C Z, Sato W, Han L, et al. Graph-based 2D road represen-tation of 3D point clouds for intelligent vehicles[C]//2011 IEEE Intelligent Vehicles Symposium (IV), Baden-Baden, Germany, 2011: 715–721.

    [13] Douillard B, Underwood J, Kuntz N, et al. On the segmentation of 3D LIDAR point clouds[C]//2011 IEEE International Confe-rence on Robotics and Automation, Shanghai, China, 2011: 2798–2805.

    [14] Zhao G Q, Yuan J S. Curb detection and tracking using 3D-LIDAR scanner[C]//2012 19th IEEE International Conference on Image Processing, Orlando, FL, USA, 2012: 437–440.

    [15] Chen T T, Dai B, Liu D X, et al. 3D LIDAR-based ground seg-mentation[C]//The First Asian Conference on Pattern Recogni-tion, Beijing, China, 2011: 446–450.

    [16] Guan HY,Yu YT,Ji Z, et al. Deep learning-based tree classifi-cation using mobile LiDAR data[J]. Remote Sensing Letters, 2015, 6(11): 864–873.

    [17] Guan HY,Yu YT,Li J, et al. Pole-like road object detection in mobile LiDAR data via supervoxel and bag-of-contextual-visual-words representation[J]. IEEE Geos-cience and Remote Sensing Letters, 2016, 13(4): 520–524.

    [18] Husain A, Vaishya R C. A time efficient algorithm for ground point filtering from mobile LiDAR data[C]//2016 International Conference on Control, Computing, Communication and Mate-rials (ICCCCM),Allahbad, India, 2016.

    [19] Montemerlo M, Becker J, Bhat S, et al. Junior: the stanford entry in the urban challenge[J]. Journal of Field Robotics, 2008, 25(9): 569–597.

    [20] Himmelsbach M, Hundelshausen F V, Wuensche H J. Fast segmentation of 3D point clouds for ground vehicles[C]//2010 IEEE Intelligent Vehicles Symposium, San Diego, CA, USA, 2010: 560–565.

    [21] Yang B S, Fang L N, Li J. Semi-automated extraction and de-lineation of 3D roads of street scene from mobile laser scanning point clouds[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013, 79: 80–93.

    [22] Hu X Y, Li X K, Zhang Y J. Fast filtering of LiDAR point cloud in urban areas based on scan line segmentation and GPU acce-leration[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(2): 308–312.

    [23] Hata A Y, Wolf D F. Feature detection for vehicle localization in urban environments using a multilayer LIDAR[J]. IEEE Transac-tions on Intelligent Transportation Systems, 2016, 17(2): 420–429.

    [24] Zhou Y, Wang D, Xie X, et al. A fast and accurate segmentation method for ordered LiDAR point cloud of large-scale scenes[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(11): 1981–1985.

    [25] Yin H L, Yang X H, He C. Spherical coordinates based methods of ground extraction and objects segmentation using 3-D LiDAR sensor[J]. IEEE Intelligent Transportation Systems Magazine, 2016, 8(1): 61–68.

    [26] Hernandez J, Marcotegui B. Filtering of artifacts and pavement segmentation from mobile LiDAR data[C]//ISPRS Workshop Laserscanning 2009, Paris, France, 2009.

    [27] Wojke N, H.selich M. Moving vehicle detection and tracking in unstructured environments[C]//2012 IEEE International Confe-rence on Robotics and Automation (ICRA), Saint Paul, MN, USA, 2012: 3082–3087.

    [29] Yuan X,Zhao CX,CaiYF, et al. Road-surface abstraction using ladar sensing[C]//2008 10th International Conference on Control, Automation, Robotics and Vision, Hanoi, Vietnam, 2008: 1097–1102.

    [30] Moosmann F, Pink O, Stiller C. Segmentation of 3D lidar data in non-flat urban environments using a local convexity crite-rion[C]//Proceedings of 2009 IEEE Intelligent Vehicles Sympo-sium, Xi'an, China, 2009: 215–220.

    [32] McElhinney C, Kumar P, Cahalane C, et al. Initial results from European road safety inspection (EURSI) mobile mapping project[C]//The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Newcastle upon Tyne, UK, 2010: 440–445.

    [33] Asvadi A, Premebida C, Peixoto P, et al. 3D lidar-based static and moving obstacle detection in driving environments: an ap-proach based on voxels and multi-region ground planes[J]. Ro-botics and Autonomous Systems, 2016, 83: 299–311.

    [34] Chen T T, Dai B, Liu D X, et al. Sparse Gaussian process re-gression based ground segmentation for autonomous land ve-hicles[C]//The 27th Chinese Control and Decision Conference, Qingdao, China, 2015: 3993–3998.

    [36] Rusu R B. Semantic 3D object maps for everyday manipulation in human living environments[J]. KI-Kstliche Intelligenz, 2010, 24(4): 345–348.

    [38] Biosca J M, Lerma J L. Unsupervised robust planar segmenta-tion of terrestrial laser scanner point clouds based on fuzzy clustering methods[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2008, 63(1): 84–98.

    [39] Zhou W Q. An object-based approach for urban land cover classification: integrating LiDAR height and intensity data[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(4): 928–931.

    [40] Tatoglu A, Pochiraju K. Point cloud segmentation with LiDAR reflection intensity behavior[C]//IEEE International Conference on Robotics and Automation, Saint Paul, MN, USA, 2012: 786–790.

    [41] Franceschi M, Teza G, Preto N, et al. Discrimination between marls and limestones using intensity data from terrestrial laser scanner[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2009, 64(6): 522–528.

    [42] Pirotti F, Guarnieri A, Vettore A. Ground filtering and vegetation mapping using multi-return terrestrial laser scanning[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013, 76: 56–63.

    [43] Boyko A, Funkhouser T. Extracting roads from dense point clouds in large scale urban environment[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2011, 66(6): S2–S12.

    [44] Song H, Choi W, Kim H. Robust vision-based rela-tive-localization approach using an RGB-depth camera and Li-DAR sensor fusion[J]. IEEE Transactions on Industrial Elec-tronics, 2016, 63(6): 3725–3736.

    [45] Lichti D D. Spectral filtering and classification of terrestrial laser scanner point clouds[J]. The Photogrammetric Record, 2005, 20(111): 218–240.

    [46] Thrun S. Learning occupancy grid maps with forward sensor models[J]. Autonomous Robots, 2003, 15(2): 111–127.

    [47] Kammel S, Ziegler J, Pitzer B, et al. Team AnnieWAY's auto-nomous system for the 2007 DARPA urban challenge[J]. Journal of Field Robotics, 2008, 25(9): 615–639.

    [48] Hoover A, Jean-Baptiste G, Jiang X, et al. An experimental comparison of range image segmentation algorithms[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996, 18(7): 673–689.

    [49] Kilian J, Haala N, Englich M. Capture and evaluation of airborne laser scanner data[C]//International Archives of Photogrammetry and Remote Sensing, Vienna, 1996, 31: 383–388.

    [50] Zhang K Q, Chen S C, Whitman D, et al. A progressive mor-phological filter for removing nonground measurements from airborne LIDAR data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(4): 872–882.

    [52] Cohen J. A coefficient of agreement for nominal scales[J]. Edu-cational and Psychological Measurement, 1960, 20(1): 37–46.

    [54] Geiger A, Lenz P,StillerC, et al. Vision meets robotics: the KITTI dataset[J]. The International Journal of Robotics Research, 2013, 32(11): 1231–1237.

    [55] Liu S D,Hu L,ShiTX, et al. Comparison of filtering algorithms for rock point cloud data[C]//Proceedings of the 2016 5th Inter-national Conference on Advanced Materials and Computer Science, 2016: 101–107.

    [56] Li J, Mei X, Prokhorov D, et al. Deep neural network for struc-tural prediction and lane detection in traffic scene[J]. IEEE Transactions on Neural Networks and Learning Systems, 2017, 28(3): 690–703.

    Huang Siyuan, Liu Limin, Dong Jian, Fu Xiongjun. Review of ground filtering algorithms for vehicle LiDAR scans point cloud data[J]. Opto-Electronic Engineering, 2020, 47(12): 190688
    Download Citation