Fast Planar Detection System Using a GPU-Based 3D Hough Transform for LiDAR Point Clouds

Plane extraction is regarded as a necessary function that supports judgment basis in many applications, including semantic digital map reconstruction and path planning for unmanned ground vehicles. Owing to the heterogeneous density and unstructured spatial distribution of three-dimensional (3D) poi...

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Vydáno v:	Applied sciences Ročník 10; číslo 5; s. 1744
Hlavní autoři:	Tian, Yifei, Song, Wei, Chen, Long, Sung, Yunsick, Kwak, Jeonghoon, Sun, Su
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.03.2020
Témata:	3d hough transform Accuracy Algorithms Efficiency lidar point clouds Methods Noise parallel computing plane extraction Principal components analysis
ISSN:	2076-3417, 2076-3417
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Abstract	Plane extraction is regarded as a necessary function that supports judgment basis in many applications, including semantic digital map reconstruction and path planning for unmanned ground vehicles. Owing to the heterogeneous density and unstructured spatial distribution of three-dimensional (3D) point clouds collected by light detection and ranging (LiDAR), plane extraction from it is recently a significant challenge. This paper proposed a parallel 3D Hough transform algorithm to realize rapid and precise plane detection from 3D LiDAR point clouds. After transforming all the 3D points from a Cartesian coordinate system to a pre-defined 3D Hough space, the generated Hough space is rasterised into a series of arranged cells to store the resided point counts into individual cells. A 3D connected component labeling algorithm is developed to cluster the cells with high values in Hough space into several clusters. The peaks from these clusters are extracted so that the targeting planar surfaces are obtained in polar coordinates. Because the laser beams emitted by LiDAR sensor holds several fixed angles, the collected 3D point clouds distribute as several horizontal and parallel circles in plane surfaces. This kind of horizontal and parallel circles mislead plane detecting results from horizontal wall surfaces to parallel planes. For detecting accurate plane parameters, this paper adopts a fraction-to-fraction method to gradually transform raw point clouds into a series of sub Hough space buffers. In our proposed planar detection algorithm, a graphic processing unit (GPU) programming technology is applied to speed up the calculation of 3D Hough space updating and peaks searching.
AbstractList	Plane extraction is regarded as a necessary function that supports judgment basis in many applications, including semantic digital map reconstruction and path planning for unmanned ground vehicles. Owing to the heterogeneous density and unstructured spatial distribution of three-dimensional (3D) point clouds collected by light detection and ranging (LiDAR), plane extraction from it is recently a significant challenge. This paper proposed a parallel 3D Hough transform algorithm to realize rapid and precise plane detection from 3D LiDAR point clouds. After transforming all the 3D points from a Cartesian coordinate system to a pre-defined 3D Hough space, the generated Hough space is rasterised into a series of arranged cells to store the resided point counts into individual cells. A 3D connected component labeling algorithm is developed to cluster the cells with high values in Hough space into several clusters. The peaks from these clusters are extracted so that the targeting planar surfaces are obtained in polar coordinates. Because the laser beams emitted by LiDAR sensor holds several fixed angles, the collected 3D point clouds distribute as several horizontal and parallel circles in plane surfaces. This kind of horizontal and parallel circles mislead plane detecting results from horizontal wall surfaces to parallel planes. For detecting accurate plane parameters, this paper adopts a fraction-to-fraction method to gradually transform raw point clouds into a series of sub Hough space buffers. In our proposed planar detection algorithm, a graphic processing unit (GPU) programming technology is applied to speed up the calculation of 3D Hough space updating and peaks searching.
Author	Chen, Long Tian, Yifei Sung, Yunsick Song, Wei Sun, Su Kwak, Jeonghoon
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Cites_doi	10.1016/j.patrec.2018.03.024 10.1109/LGRS.2013.2246134 10.1016/j.isprsjprs.2013.05.006 10.1016/j.isprsjprs.2015.01.011 10.3390/rs9050433 10.1016/j.robot.2016.06.007 10.1016/j.jvcir.2013.04.001 10.22260/ISARC2016/0044 10.1016/j.isprsjprs.2014.07.004 10.1016/j.patrec.2010.10.009 10.1109/ICCKE.2015.7365845 10.5194/isprsarchives-XL-3-1-2014 10.1049/iet-ipr.2017.1076 10.1016/j.autcon.2018.01.009 10.1016/j.robot.2016.11.014 10.1016/j.patcog.2014.12.020 10.1016/j.patrec.2017.12.027 10.1109/CCDC.2018.8407394 10.1109/TCYB.2014.2316282 10.1016/j.robot.2014.08.019 10.1108/IR-04-2013-347 10.5220/0005679003450352 10.1186/s13673-017-0120-7
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References	Awrangjeb (ref_4) 2013; 83 Deschaud (ref_13) 2014; 25 Limberger (ref_6) 2015; 48 Marriott (ref_26) 2018; 110 Nurunnabi (ref_16) 2014; 96 Asvadi (ref_1) 2016; 83 Galloa (ref_18) 2011; 32 Wang (ref_5) 2017; 88 Whelan (ref_15) 2015; 69 Song (ref_28) 2017; 7 Qian (ref_19) 2014; 44 Kim (ref_3) 2018; 89 ref_24 ref_22 ref_21 Yeon (ref_17) 2014; 41 ref_20 Vera (ref_23) 2018; 103 Maltezos (ref_25) 2018; 19 Sayed (ref_7) 2018; 12 Liang (ref_11) 2014; 11 Ramiya (ref_2) 2017; 20 Abdullah (ref_12) 2014; 3 Vo (ref_14) 2015; 104 ref_27 ref_9 ref_8 Ferruz (ref_29) 2014; 43 Hulik (ref_10) 2014; 25
References_xml	– volume: 110 start-page: 44 year: 2018 ident: ref_26 article-title: Plane-Extraction from depth-data using a Gaussian mixture regression model publication-title: Pattern Recogn. Lett. doi: 10.1016/j.patrec.2018.03.024 – volume: 11 start-page: 69 year: 2014 ident: ref_11 article-title: Automatic registration of terrestrial laser scanning data using precisely located artificial planar targets publication-title: IEEE Geosci. Remote Sens. doi: 10.1109/LGRS.2013.2246134 – ident: ref_9 – volume: 19 start-page: 562 year: 2018 ident: ref_25 article-title: Plane detection of polyhedral cultural heritage monuments: The case of tower of winds in Athens publication-title: J. Archaeol. Sci. Rep. – volume: 83 start-page: 1 year: 2013 ident: ref_4 article-title: Automatic extraction of building roofs using LIDAR data and multispectral imagery publication-title: ISPRS J. Photogramm. doi: 10.1016/j.isprsjprs.2013.05.006 – volume: 104 start-page: 88 year: 2015 ident: ref_14 article-title: Octree-Based region growing for point cloud segmentation publication-title: ISPRS J. Photogramm. doi: 10.1016/j.isprsjprs.2015.01.011 – ident: ref_21 doi: 10.3390/rs9050433 – volume: 83 start-page: 299 year: 2016 ident: ref_1 article-title: 3D Lidar-based static and moving obstacle detection in driving environments: An approach based on voxels and multi-region ground planes publication-title: Robot. Auton. Syst. doi: 10.1016/j.robot.2016.06.007 – volume: 43 start-page: 703 year: 2014 ident: ref_29 article-title: A Comparative study of parallel RANSAC implementations in 3D space publication-title: Int. J. Parallel Program. – volume: 25 start-page: 86 year: 2014 ident: ref_10 article-title: Continuous plane detection in point-cloud data based on 3D Hough Transform publication-title: J. Vis. Commun. Image doi: 10.1016/j.jvcir.2013.04.001 – ident: ref_8 doi: 10.22260/ISARC2016/0044 – volume: 96 start-page: 106 year: 2014 ident: ref_16 article-title: Robust statistical approaches for local planar surface fitting in 3D laser scanning data publication-title: ISPRS J. Photogramm. doi: 10.1016/j.isprsjprs.2014.07.004 – volume: 32 start-page: 403 year: 2011 ident: ref_18 article-title: CC-RANSAC: Fitting planes in the presence of multiple surfaces in range data publication-title: Pattern Recogn. Lett. doi: 10.1016/j.patrec.2010.10.009 – ident: ref_22 doi: 10.1109/ICCKE.2015.7365845 – volume: 3 start-page: 1 year: 2014 ident: ref_12 article-title: LiDAR segmentation using suitable seed points for 3D building extraction publication-title: Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. doi: 10.5194/isprsarchives-XL-3-1-2014 – volume: 12 start-page: 1595 year: 2018 ident: ref_7 article-title: Plane detection in 3D point cloud using octree-balanced density down-sampling and iterative adaptive plane extraction publication-title: IET Image Process. doi: 10.1049/iet-ipr.2017.1076 – volume: 89 start-page: 38 year: 2018 ident: ref_3 article-title: SLAM-Driven robotic mapping and registration of 3D point clouds publication-title: Autom. Constr. doi: 10.1016/j.autcon.2018.01.009 – ident: ref_27 – volume: 88 start-page: 71 year: 2017 ident: ref_5 article-title: Pedestrian recognition and tracking using 3D LiDAR for autonomous vehicle publication-title: Robot. Auton. Syst. doi: 10.1016/j.robot.2016.11.014 – volume: 48 start-page: 2043 year: 2015 ident: ref_6 article-title: Real-Time detection of planar regions in unorganized point clouds publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2014.12.020 – volume: 103 start-page: 8 year: 2018 ident: ref_23 article-title: Hough transform for real-time plane detection in depth images publication-title: Pattern Recogn Lett. doi: 10.1016/j.patrec.2017.12.027 – volume: 25 start-page: 86 year: 2014 ident: ref_13 article-title: A Fast and accurate plane detection algorithm for large noisy point clouds using filtered normals and voxel growing publication-title: J. Vis. Commun. Image Represent. – ident: ref_20 doi: 10.1109/CCDC.2018.8407394 – volume: 20 start-page: 71 year: 2017 ident: ref_2 article-title: Segmentation based building detection approach from LiDAR point cloud publication-title: Egypt. J. Remote Sens. Space Sci. – volume: 44 start-page: 2771 year: 2014 ident: ref_19 article-title: NCC-RANSAC: A fast plane extraction method for 3-D range data segmentation publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2014.2316282 – volume: 69 start-page: 3 year: 2015 ident: ref_15 article-title: Incremental and batch planar simplification of dense point cloud maps publication-title: Robot. Auton. Syst. doi: 10.1016/j.robot.2014.08.019 – volume: 41 start-page: 203 year: 2014 ident: ref_17 article-title: Robust-PCA-based hierarchical plane extraction for application to geometric 3D indoor mapping publication-title: Ind. Robot. doi: 10.1108/IR-04-2013-347 – ident: ref_24 doi: 10.5220/0005679003450352 – volume: 7 start-page: 39 year: 2017 ident: ref_28 article-title: A 3D localisation method in indoor environments for virtual reality applications publication-title: Hum. Centric Comput. Inf. Sci. doi: 10.1186/s13673-017-0120-7
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SubjectTerms	3d hough transform Accuracy Algorithms Efficiency lidar point clouds Methods Noise parallel computing plane extraction Principal components analysis
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Title	Fast Planar Detection System Using a GPU-Based 3D Hough Transform for LiDAR Point Clouds
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