{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T11:15:50Z","timestamp":1762254950188,"version":"3.37.3"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2024,8,11]],"date-time":"2024-08-11T00:00:00Z","timestamp":1723334400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,8,11]],"date-time":"2024-08-11T00:00:00Z","timestamp":1723334400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62172247"],"award-info":[{"award-number":["62172247"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Machine Vision and Applications"],"published-print":{"date-parts":[[2024,9]]},"DOI":"10.1007\/s00138-024-01593-5","type":"journal-article","created":{"date-parts":[[2024,8,11]],"date-time":"2024-08-11T12:01:59Z","timestamp":1723377719000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An efficient ground segmentation approach for LiDAR point cloud utilizing adjacent grids"],"prefix":"10.1007","volume":"35","author":[{"given":"Longyu","family":"Dong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dejun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Youqiang","family":"Dong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bongrae","family":"Park","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhibo","family":"Wan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,11]]},"reference":[{"key":"1593_CR1","doi-asserted-by":"crossref","unstructured":"Douillard, B., Underwood, J., Kuntz, N., Vlaskine, V., Quadros, A., Morton, P., Frenkel, A.: On the segmentation of 3d lidar point clouds. In: 2011 IEEE International Conference on Robotics and Automation, pp. 2798\u20132805. IEEE (2011)","DOI":"10.1109\/ICRA.2011.5979818"},{"key":"1593_CR2","doi-asserted-by":"crossref","unstructured":"Asvadi, A., Peixoto, P., Nunes, U.: Detection and tracking of moving objects using 2.5 d motion grids. In: 2015 IEEE 18th International Conference on Intelligent Transportation Systems, pp. 788\u2013793. IEEE (2015)","DOI":"10.1109\/ITSC.2015.133"},{"issue":"4","key":"1593_CR3","doi-asserted-by":"publisher","first-page":"6458","DOI":"10.1109\/LRA.2021.3093009","volume":"6","author":"H Lim","year":"2021","unstructured":"Lim, H., Oh, M., Myung, H.: Patchwork: concentric zone-based region-wise ground segmentation with ground likelihood estimation using a 3d lidar sensor. IEEE Robot. Autom. Lett. 6(4), 6458\u20136465 (2021)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"1593_CR4","doi-asserted-by":"crossref","unstructured":"Behley, J., Garbade, M., Milioto, A., Quenzel, J., Behnke, S., Stachniss, C., Gall, J.: Semantickitti: a dataset for semantic scene understanding of lidar sequences. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9297\u20139307 (2019)","DOI":"10.1109\/ICCV.2019.00939"},{"issue":"2","key":"1593_CR5","doi-asserted-by":"publisher","first-page":"1357","DOI":"10.1109\/JSEN.2022.3225293","volume":"23","author":"D Guo","year":"2022","unstructured":"Guo, D., Yang, G., Qi, B., Wang, C.: A fast ground segmentation method of lidar point cloud from coarse-to-fine. IEEE Sens. J. 23(2), 1357\u20131367 (2022)","journal-title":"IEEE Sens. J."},{"key":"1593_CR6","doi-asserted-by":"crossref","unstructured":"Xu, J., Zhang, R., Dou, J., Zhu, Y., Sun, J., Pu, S.: Rpvnet: a deep and efficient range-point-voxel fusion network for lidar point cloud segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 16024\u201316033 (2021)","DOI":"10.1109\/ICCV48922.2021.01572"},{"issue":"16","key":"1593_CR7","doi-asserted-by":"publisher","first-page":"3239","DOI":"10.3390\/rs13163239","volume":"13","author":"Z Shen","year":"2021","unstructured":"Shen, Z., Liang, H., Lin, L., Wang, Z., Huang, W., Yu, J.: Fast ground segmentation for 3d lidar point cloud based on jump-convolution-process. Remote Sens. 13(16), 3239 (2021)","journal-title":"Remote Sens."},{"key":"1593_CR8","doi-asserted-by":"crossref","unstructured":"Paigwar, A., Erkent, \u00d6., Sierra-Gonzalez, D., Laugier, C.: Gndnet: fast ground plane estimation and point cloud segmentation for autonomous vehicles. In: 2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2150\u20132156. IEEE (2020)","DOI":"10.1109\/IROS45743.2020.9340979"},{"key":"1593_CR9","unstructured":"Qi, C.R., Su, H., Mo, K., Guibas, L.J.: Pointnet: Deep learning on point sets for 3d classification and segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 652\u2013660 (2017)"},{"key":"1593_CR10","doi-asserted-by":"crossref","unstructured":"Himmelsbach, M., Hundelshausen, F.V., Wuensche, H.-J.: Fast segmentation of 3d point clouds for ground vehicles. In: 2010 IEEE Intelligent Vehicles Symposium, pp. 560\u2013565. IEEE (2010)","DOI":"10.1109\/IVS.2010.5548059"},{"key":"1593_CR11","doi-asserted-by":"crossref","unstructured":"Zermas, D., Izzat, I., Papanikolopoulos, N.: Fast segmentation of 3d point clouds: a paradigm on lidar data for autonomous vehicle applications. In: 2017 IEEE International Conference on Robotics and Automation (ICRA), pp. 5067\u20135073. IEEE (2017)","DOI":"10.1109\/ICRA.2017.7989591"},{"issue":"6","key":"1593_CR12","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381\u2013395 (1981)","journal-title":"Commun. ACM"},{"issue":"2","key":"1593_CR13","doi-asserted-by":"publisher","first-page":"2272","DOI":"10.1109\/LRA.2021.3061363","volume":"6","author":"H Lim","year":"2021","unstructured":"Lim, H., Hwang, S., Myung, H.: Erasor: egocentric ratio of pseudo occupancy-based dynamic object removal for static 3d point cloud map building. IEEE Robot. Autom. Lett. 6(2), 2272\u20132279 (2021)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"1593_CR14","doi-asserted-by":"publisher","first-page":"132914","DOI":"10.1109\/ACCESS.2021.3115664","volume":"9","author":"V Jim\u00e9nez","year":"2021","unstructured":"Jim\u00e9nez, V., Godoy, J., Artu\u00f1edo, A., Villagra, J.: Ground segmentation algorithm for sloped terrain and sparse lidar point cloud. IEEE Access 9, 132914\u2013132927 (2021)","journal-title":"IEEE Access"},{"issue":"2","key":"1593_CR15","doi-asserted-by":"publisher","first-page":"1597","DOI":"10.1109\/TIV.2022.3187008","volume":"8","author":"Y Qian","year":"2022","unstructured":"Qian, Y., Wang, X., Chen, Z., Wang, C., Yang, M.: Hy-seg: a hybrid method for ground segmentation using point clouds. IEEE Trans. Intell. Veh. 8(2), 1597\u20131606 (2022)","journal-title":"IEEE Trans. Intell. Veh."},{"key":"1593_CR16","doi-asserted-by":"crossref","unstructured":"Lee, S., Lim, H., Myung, H.: Patchwork++: fast and robust ground segmentation solving partial under-segmentation using 3d point cloud. In: 2022 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 13276\u201313283. IEEE (2022)","DOI":"10.1109\/IROS47612.2022.9981561"},{"issue":"3","key":"1593_CR17","doi-asserted-by":"publisher","first-page":"7255","DOI":"10.1109\/LRA.2022.3182096","volume":"7","author":"M Oh","year":"2022","unstructured":"Oh, M., Jung, E., Lim, H., Song, W., Hu, S., Lee, E.M., Park, J., Kim, J., Lee, J., Myung, H.: Travel: traversable ground and above-ground object segmentation using graph representation of 3d lidar scans. IEEE Robot. Autom. Lett. 7(3), 7255\u20137262 (2022)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"1593_CR18","doi-asserted-by":"crossref","unstructured":"Shan, T., Englot, B.: Lego-loam: Lightweight and ground-optimized lidar odometry and mapping on variable terrain. In: 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4758\u20134765. IEEE (2018)","DOI":"10.1109\/IROS.2018.8594299"},{"key":"1593_CR19","doi-asserted-by":"crossref","unstructured":"Pan, Y., Xiao, P., He, Y., Shao, Z., Li, Z.: Mulls: Versatile lidar slam via multi-metric linear least square. In: 2021 IEEE International Conference on Robotics and Automation (ICRA), pp. 11633\u201311640. IEEE (2021)","DOI":"10.1109\/ICRA48506.2021.9561364"},{"key":"1593_CR20","doi-asserted-by":"crossref","unstructured":"Seo, D.-U., Lim, H., Lee, S., Myung, H.: Pago-loam: robust ground-optimized lidar odometry. In: 2022 19th International Conference on Ubiquitous Robots (UR), pp. 1\u20137. IEEE (2022)","DOI":"10.1109\/UR55393.2022.9826238"},{"issue":"4","key":"1593_CR21","doi-asserted-by":"publisher","first-page":"12086","DOI":"10.1109\/LRA.2022.3201689","volume":"7","author":"Z Wang","year":"2022","unstructured":"Wang, Z., Yang, L., Gao, F., Wang, L.: Fevo-loam: feature extraction and vertical optimized lidar odometry and mapping. IEEE Robot. Autom. Lett. 7(4), 12086\u201312093 (2022)","journal-title":"IEEE Robot. Autom. Lett."},{"issue":"5","key":"1593_CR22","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1177\/02783649231207654","volume":"43","author":"H Lim","year":"2024","unstructured":"Lim, H., Kim, B., Kim, D., Mason Lee, E., Myung, H.: Quatro++: robust global registration exploiting ground segmentation for loop closing in lidar slam. Int. J. Robot. Res. 43(5), 685\u2013715 (2024)","journal-title":"Int. J. Robot. Res."},{"key":"1593_CR23","doi-asserted-by":"crossref","unstructured":"Yang, H., Shi, J., Carlone, L.: TEASER: fast and certifiable point cloud registration. IEEE Trans. Robot. (2020)","DOI":"10.1109\/TRO.2020.3033695"},{"key":"1593_CR24","doi-asserted-by":"crossref","unstructured":"Narksri, P., Takeuchi, E., Ninomiya, Y., Morales, Y., Akai, N., Kawaguchi, N.: A slope-robust cascaded ground segmentation in 3d point cloud for autonomous vehicles. In: 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 497\u2013504. IEEE (2018)","DOI":"10.1109\/ITSC.2018.8569534"}],"container-title":["Machine Vision and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00138-024-01593-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00138-024-01593-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00138-024-01593-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T04:04:44Z","timestamp":1726027484000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00138-024-01593-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,11]]},"references-count":24,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,9]]}},"alternative-id":["1593"],"URL":"https:\/\/doi.org\/10.1007\/s00138-024-01593-5","relation":{},"ISSN":["0932-8092","1432-1769"],"issn-type":[{"type":"print","value":"0932-8092"},{"type":"electronic","value":"1432-1769"}],"subject":[],"published":{"date-parts":[[2024,8,11]]},"assertion":[{"value":"19 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 July 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 July 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 August 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no relevant financial or non-financial interests to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"108"}}