{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T03:42:30Z","timestamp":1772077350982,"version":"3.50.1"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2023,5,28]],"date-time":"2023-05-28T00:00:00Z","timestamp":1685232000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,5,28]],"date-time":"2023-05-28T00:00:00Z","timestamp":1685232000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100003392","name":"Natural Science Foundation of Fujian Province","doi-asserted-by":"publisher","award":["2021J01540"],"award-info":[{"award-number":["2021J01540"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003392","name":"Natural Science Foundation of Fujian Province","doi-asserted-by":"publisher","award":["2021J05106"],"award-info":[{"award-number":["2021J05106"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62032022"],"award-info":[{"award-number":["62032022"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62176244"],"award-info":[{"award-number":["62176244"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62006215"],"award-info":[{"award-number":["62006215"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2023,11]]},"DOI":"10.1007\/s13042-023-01863-0","type":"journal-article","created":{"date-parts":[[2023,5,28]],"date-time":"2023-05-28T08:02:01Z","timestamp":1685260921000},"page":"3765-3781","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A new method for two-stage partial-to-partial 3D point cloud registration: multi-level interaction perception"],"prefix":"10.1007","volume":"14","author":[{"given":"Xinhong","family":"Meng","sequence":"first","affiliation":[]},{"given":"Lei","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Hailiang","family":"Ye","sequence":"additional","affiliation":[]},{"given":"Feilong","family":"Cao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,5,28]]},"reference":[{"issue":"8","key":"1863_CR1","doi-asserted-by":"publisher","first-page":"3412","DOI":"10.1109\/TNNLS.2020.3015992","volume":"32","author":"Y Li","year":"2020","unstructured":"Li Y, Ma LF, Zhong ZL, Liu F, Chapman MA, Cao DP, Li J (2020) Deep learning for LiDAR point clouds in autonomous driving: a review. IEEE Trans Neural Netw Learn Syst 32(8):3412\u20133432","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"1863_CR2","doi-asserted-by":"publisher","first-page":"722","DOI":"10.1109\/TITS.2020.3023541","volume":"23","author":"YD Cui","year":"2021","unstructured":"Cui YD, Chen R, Chu WB, Chen L, Tian DX, Li Y, Cao DP (2021) Deep learning for image and point cloud fusion in autonomous driving: a review. IEEE Trans Intell Transp Syst 23:722\u2013739","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"1863_CR3","doi-asserted-by":"crossref","unstructured":"He YS, Huang HB, Fan HQ, Chen QF, Sun J (2021) FFB6D: A full flow bidirectional fusion network for 6D pose estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 3003\u20133013","DOI":"10.1109\/CVPR46437.2021.00302"},{"key":"1863_CR4","doi-asserted-by":"publisher","first-page":"5072","DOI":"10.1109\/TIP.2021.3078109","volume":"30","author":"JW Guo","year":"2021","unstructured":"Guo JW, Xing XJ, Quan WZ, Yan DM, Gu QY, Liu Y, Zhang XP (2021) Efficient center voting for object detection and 6D pose estimation in 3D point cloud. IEEE Trans Image Process 30:5072\u20135084","journal-title":"IEEE Trans Image Process"},{"key":"1863_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108210","volume":"121","author":"YQ Xu","year":"2022","unstructured":"Xu YQ, Jung C, Chang YK (2022) Head pose estimation using deep neural networks and 3D point clouds. Pattern Recogn 121:108210","journal-title":"Pattern Recogn"},{"issue":"4","key":"1863_CR6","doi-asserted-by":"publisher","first-page":"3843","DOI":"10.1109\/TIE.2021.3070497","volume":"69","author":"YF Yue","year":"2021","unstructured":"Yue YF, Wen MX, Zhao CY, Wang YZ, Wang DW (2021) COSEM: collaborative semantic map matching framework for autonomous robots. IEEE Trans Industr Electron 69(4):3843\u20133853","journal-title":"IEEE Trans Industr Electron"},{"key":"1863_CR7","doi-asserted-by":"crossref","unstructured":"Cai QL, Chen KW, Yao CH, Chu HK (2021) Automatic local point cloud registration algorithm and point cloud reconstruction system. In: Proceedings of the IEEE International Symposium on Intelligent Signal Processing and Communication Systems, pp 1\u20132","DOI":"10.1109\/ISPACS51563.2021.9651113"},{"key":"1863_CR8","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1016\/j.isprsjprs.2021.08.019","volume":"180","author":"RC Shinde","year":"2021","unstructured":"Shinde RC, Durbha SS, Potnis AV (2021) LidarCSNet: a deep convolutional compressive sensing reconstruction framework for 3D airborne lidar point cloud. ISPRS J Photogramm Remote Sens 180:313\u2013334","journal-title":"ISPRS J Photogramm Remote Sens"},{"issue":"1","key":"1863_CR9","first-page":"1","volume":"2","author":"B Alsadik","year":"2021","unstructured":"Alsadik B, Karam S (2021) The simultaneous localization and mapping (SLAM) - An overview. Surv Geospat Eng J 2(1):1\u201312","journal-title":"Surv Geospat Eng J"},{"key":"1863_CR10","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1146\/annurev-control-072720-082553","volume":"4","author":"DM Rosen","year":"2021","unstructured":"Rosen DM, Doherty KJ, Ter\u00e1n Espinoza A, Leonard JJ (2021) Advances in inference and representation for simultaneous localization and mapping. Ann Rev Control Robot Auton Syst 4:215\u2013242","journal-title":"Ann Rev Control Robot Auton Syst"},{"key":"1863_CR11","doi-asserted-by":"crossref","unstructured":"Li HD, Hartley R (2007) The 3D-3D registration problem revisited. In: Proceedings of the IEEE international conference on computer vision, Rio de Janeiro, Brazil, pp 1\u20138","DOI":"10.1109\/ICCV.2007.4409077"},{"key":"1863_CR12","doi-asserted-by":"crossref","unstructured":"Aoki Y, Goforth H, Srivatsan RA, Lucey S (2019) PointNetLK: Robust & efficient point cloud registration using PointNet. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Long Beach, USA, pp 7163\u20137172","DOI":"10.1109\/CVPR.2019.00733"},{"key":"1863_CR13","doi-asserted-by":"crossref","unstructured":"Wang Y, Solomon JM (2019a) Deep closest point: Learning representations for point cloud registration. In: Proceedings of the IEEE International Conference on Computer Vision, Long Beach, USA, pp 3523\u20133532","DOI":"10.1109\/ICCV.2019.00362"},{"key":"1863_CR14","unstructured":"Wang Y, Solomon JM (2019b) PRNet: Self-supervised learning for partial-to-partial registration. In: Proceedings of the Advances in Neural Information Processing Systems, Vancouver, Canada, p 8814-8826"},{"key":"1863_CR15","doi-asserted-by":"crossref","unstructured":"Li JH, Zhang CH, Xu ZY, Zhou HN, Zhang C (2020) Iterative distance-aware similarity matrix convolution with mutual-supervised point elimination for efficient point cloud registration. In: Proceedings of the European Conference on Computer Vision, pp 378\u2013394","DOI":"10.1007\/978-3-030-58586-0_23"},{"key":"1863_CR16","doi-asserted-by":"crossref","unstructured":"Yew ZJ, Lee GH (2020) RPMNet: Robust point matching using learned features. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 11824\u201311833","DOI":"10.1109\/CVPR42600.2020.01184"},{"key":"1863_CR17","doi-asserted-by":"crossref","unstructured":"Fu K, Liu S, Luo X, Wang M (2021) Robust point cloud registration framework based on deep graph matching. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 8893\u20138902","DOI":"10.1109\/CVPR46437.2021.00878"},{"key":"1863_CR18","unstructured":"Qi CR, Su H, Mo K, Guibas LJ (2017) PointNet: Deep learning on point sets for 3D classification and segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, USA, pp 77\u201385"},{"key":"1863_CR19","doi-asserted-by":"crossref","unstructured":"Huang SY, Gojcic Z, Usvyatsov M, Wieser A, Schindler K (2021) PREDATOR: Registration of 3D point clouds with low overlap. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 4267\u20134276","DOI":"10.1109\/CVPR46437.2021.00425"},{"key":"1863_CR20","unstructured":"Zhu LF, Liu D, Lin CW, Yan R, G\u00f3mez-Fern\u00e1ndez F, Yang NH, Feng ZY (2021) Point cloud registration using representative overlapping points, arXiv preprint arXiv:2107.02583"},{"issue":"2","key":"1863_CR21","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1109\/34.121791","volume":"14","author":"B PaulJ","year":"1992","unstructured":"PaulJ B, NeilD M (1992) A method for registration of 3D shapes. IEEE Trans Pattern Anal Mach Intell 14(2):239\u2013256","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1863_CR22","doi-asserted-by":"crossref","unstructured":"Rusinkiewicz S, Levoy M (2001) Efficient variants of the ICP algorithm. In: Proceedings of the International Conference on 3D Digital Imaging and Modeling, Quebec City, Canada, pp 145\u2013152","DOI":"10.1109\/IM.2001.924423"},{"issue":"13\u201314","key":"1863_CR23","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.1016\/j.imavis.2003.09.004","volume":"21","author":"AW Fitzgibbon","year":"2003","unstructured":"Fitzgibbon AW (2003) Robust registration of 2D and 3D point sets. Image Vis Comput 21(13\u201314):1145\u20131153","journal-title":"Image Vis Comput"},{"issue":"11","key":"1863_CR24","doi-asserted-by":"publisher","first-page":"2241","DOI":"10.1109\/TPAMI.2015.2513405","volume":"38","author":"JL Yang","year":"2015","unstructured":"Yang JL, Li HD, Campbell D, Jia YD (2015) Go-ICP: a globally optimal solution to 3D ICP point-set registration. IEEE Trans Pattern Anal Mach Intell 38(11):2241\u20132254","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1863_CR25","doi-asserted-by":"crossref","unstructured":"Zhou QY, Park J, Koltun V (2016) Fast global registration. In: Proceedings of the European Conference on Computer Vision, Amsterdam, The Netherlands, pp 766\u2013782","DOI":"10.1007\/978-3-319-46475-6_47"},{"key":"1863_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/LGRS.2021.3099166","volume":"19","author":"J Qian","year":"2021","unstructured":"Qian J, Chen KQ, Chen QY, Yang YH, Zhang JH, Chen SY (2021) Robust visual-lidar simultaneous localization and mapping system for UAV. IEEE Geosci Remote Sens Lett 19:1\u20135","journal-title":"IEEE Geosci Remote Sens Lett"},{"key":"1863_CR27","doi-asserted-by":"crossref","unstructured":"Eckart B, Kim K, Kautz J (2018) HGMR: Hierarchical gaussian mixtures for adaptive 3D registration. In: Proceedings of the European Conference on Computer Vision, Munich, Germany, pp 705\u2013721","DOI":"10.1007\/978-3-030-01267-0_43"},{"key":"1863_CR28","doi-asserted-by":"crossref","unstructured":"Campbell D, Petersson L (2016) GOGMA: Globally-optimal gaussian mixture alignment. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, USA, pp 5685\u20135694","DOI":"10.1109\/CVPR.2016.613"},{"issue":"1","key":"1863_CR29","first-page":"2","volume":"4","author":"KG Derpanis","year":"2010","unstructured":"Derpanis KG (2010) Overview of the RANSAC algorithm. Image Rochester NY 4(1):2\u20133","journal-title":"Image Rochester NY"},{"key":"1863_CR30","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1016\/j.isprsjprs.2020.07.012","volume":"167","author":"JY Li","year":"2020","unstructured":"Li JY, Hu QW, Ai MY (2020) GESAC: robust graph enhanced sample consensus for point cloud registration. ISPRS J Photogramm Remote Sens 167:363\u2013374","journal-title":"ISPRS J Photogramm Remote Sens"},{"issue":"11","key":"1863_CR31","doi-asserted-by":"publisher","first-page":"9716","DOI":"10.1109\/TGRS.2020.3045456","volume":"59","author":"JY Li","year":"2021","unstructured":"Li JY, Hu QW, Ai MY (2021) Point cloud registration based on one-point RANSAC and scale-annealing biweight estimation. IEEE Trans Geosci Remote Sens 59(11):9716\u20139729","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"5","key":"1863_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3326362","volume":"38","author":"Y Wang","year":"2019","unstructured":"Wang Y, Sun Y, Liu ZW, Sarma SE, Bronstein MM, Solomon JM (2019) Dynamic graph CNN for learning on point clouds. ACM Trans Graph 38(5):1\u201312","journal-title":"ACM Trans Graph"},{"key":"1863_CR33","unstructured":"Sarode V, Li XQ, Goforth H, Aoki Y, Srivatsan RA, Lucey S, Choset H (2019) PCRNet: Point cloud registration network using PointNet encoding, arXiv preprint arXiv:1908.07906"},{"issue":"3","key":"1863_CR34","doi-asserted-by":"publisher","first-page":"3960","DOI":"10.1109\/LRA.2020.2970946","volume":"5","author":"A Kurobe","year":"2020","unstructured":"Kurobe A, Sekikawa Y, Ishikawa K, Saito H (2020) CorsNet: 3D point cloud registration by deep neural network. IEEE Robot Autom Lett 5(3):3960\u20133966","journal-title":"IEEE Robot Autom Lett"},{"issue":"2","key":"1863_CR35","doi-asserted-by":"publisher","first-page":"2533","DOI":"10.1109\/LRA.2021.3061369","volume":"6","author":"HW Zhao","year":"2021","unstructured":"Zhao HW, Liang ZD, Wang CX, Yang M (2021) CentroidReg: a global-to-local framework for partial point cloud registration. IEEE Robot Autom Lett 6(2):2533\u20132540","journal-title":"IEEE Robot Autom Lett"},{"key":"1863_CR36","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1016\/j.isprsjprs.2021.03.003","volume":"175","author":"ZH Zhang","year":"2021","unstructured":"Zhang ZH, Chen GL, Wang X, Shu MC (2021) DDRNet: fast point cloud registration network for large-scale scenes. ISPRS J Photogramm Remote Sens 175:184\u2013198","journal-title":"ISPRS J Photogramm Remote Sens"},{"key":"1863_CR37","doi-asserted-by":"crossref","unstructured":"Xu H, Liu SC, Wang GF, Liu GH, Zeng B (2021) OMNet: Learning overlapping mask for partial-to-partial point cloud registration. In: Proceedings of the IEEE International Conference on Computer Vision, pp 3132\u20133141","DOI":"10.1109\/ICCV48922.2021.00312"},{"issue":"1","key":"1863_CR38","doi-asserted-by":"publisher","first-page":"1135","DOI":"10.1109\/TPAMI.2022.3148308","volume":"45","author":"YJ Wang","year":"2022","unstructured":"Wang YJ, Yan CG, Feng YT, Du SY, Dai QH, Gao Y (2022) STORM: structure-based overlap matching for partial point cloud registration. IEEE Trans Pattern Anal Mach Intell 45(1):1135\u20131149","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1863_CR39","unstructured":"Zagoruyko S, Komodakis N (2017) Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer. In: Proceedings of the International Conference on Learning Representations, Palais, France"},{"key":"1863_CR40","doi-asserted-by":"crossref","unstructured":"Woo S, Park J, Lee JY, Kweon IS (2018) CBAM: Convolutional block attention module. In: Proceedings of the European Conference on Computer Cision, Munich, Germany, pp 3\u201319","DOI":"10.1007\/978-3-030-01234-2_1"},{"issue":"2","key":"1863_CR41","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1007\/s41095-021-0229-5","volume":"7","author":"MH Guo","year":"2021","unstructured":"Guo MH, Cai JX, Liu ZN, Mu TJ, Martin RR, Hu SM (2021) PCT: Point cloud transformer. Computational Visual Media 7(2):187\u2013199","journal-title":"Computational Visual Media"},{"key":"1863_CR42","unstructured":"Wu ZR, Song S, Khosla A, Yu F, Zhang LG, Tang XO, Xiao JX (2015) 3D ShapeNets: A deep representation for volumetric shapes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 1912\u20131920"},{"key":"1863_CR43","doi-asserted-by":"crossref","unstructured":"Hezroni I, Drory A, Giryes R, Avidan S (2021) DeepBBS: Deep best buddies for point cloud registration. In: Proceedings of the IEEE International Conference on 3D Vision, pp 342\u2013351","DOI":"10.1109\/3DV53792.2021.00044"},{"issue":"2","key":"1863_CR44","doi-asserted-by":"publisher","first-page":"1623","DOI":"10.1007\/s00521-021-06464-y","volume":"34","author":"H Wang","year":"2022","unstructured":"Wang H, Liu X, Kang W, Yan Z, Wang B, Ning Q (2022) Multi-features guidance network for partial-to-partial point cloud registration. Neural Comput Appl 34(2):1623\u20131634","journal-title":"Neural Comput Appl"},{"key":"1863_CR45","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109523","volume":"253","author":"B Sang","year":"2022","unstructured":"Sang B, Chen H, Wan J, Yang L, Li T, Xu W, Luo C (2022) Self-adaptive weighted interaction feature selection based on robust fuzzy dominance rough sets for monotonic classification. Knowl-Based Syst 253:109523","journal-title":"Knowl-Based Syst"},{"issue":"6","key":"1863_CR46","doi-asserted-by":"publisher","first-page":"1683","DOI":"10.1109\/TFUZZ.2021.3064686","volume":"30","author":"B Sang","year":"2021","unstructured":"Sang B, Chen H, Yang L, Li T, Xu W (2021) Incremental feature selection using a conditional entropy based on fuzzy dominance neighborhood rough sets. IEEE Trans Fuzzy Syst 30(6):1683\u20131697","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"12","key":"1863_CR47","doi-asserted-by":"publisher","first-page":"5181","DOI":"10.1109\/TFUZZ.2022.3169625","volume":"30","author":"B Sang","year":"2022","unstructured":"Sang B, Chen H, Yang L, Wan J, Li T, Xu W (2022) Feature selection considering multiple correlations based on soft fuzzy dominance rough sets for monotonic classification. IEEE Trans Fuzzy Syst 30(12):5181\u20135195","journal-title":"IEEE Trans Fuzzy Syst"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-023-01863-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-023-01863-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-023-01863-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T04:10:32Z","timestamp":1695787832000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-023-01863-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,28]]},"references-count":47,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2023,11]]}},"alternative-id":["1863"],"URL":"https:\/\/doi.org\/10.1007\/s13042-023-01863-0","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,28]]},"assertion":[{"value":"26 January 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 May 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 May 2023","order":3,"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 competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}