{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T03:17:33Z","timestamp":1781925453531,"version":"3.54.5"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2025,1,29]],"date-time":"2025-01-29T00:00:00Z","timestamp":1738108800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,29]],"date-time":"2025-01-29T00:00:00Z","timestamp":1738108800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1007\/s10489-025-06296-6","type":"journal-article","created":{"date-parts":[[2025,1,29]],"date-time":"2025-01-29T00:20:11Z","timestamp":1738110011000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Multi-view human point cloud registration method with overlapping regions semantic constraints and feature weighting"],"prefix":"10.1007","volume":"55","author":[{"given":"Ming","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guiqin","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xihang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tiancai","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,1,29]]},"reference":[{"key":"6296_CR1","doi-asserted-by":"crossref","unstructured":"Yu Z, Yang L, Chen S, Yao A (2021) Local and global point cloud reconstruction for 3d hand pose estimation. arXiv:2112.06389","DOI":"10.5244\/C.35.239"},{"key":"6296_CR2","doi-asserted-by":"crossref","unstructured":"Saito S, Huang Z, Natsume R, Morishima S, Kanazawa A, Li H (2019) Pifu: pixel-aligned implicit function for high-resolution clothed human digitization. In: Proceedings of the IEEE\/CVF international conference on computer vision pp 2304\u20132314","DOI":"10.1109\/ICCV.2019.00239"},{"issue":"6","key":"6296_CR3","doi-asserted-by":"publisher","first-page":"6739","DOI":"10.1007\/s10489-021-02783-8","volume":"52","author":"Z Li","year":"2022","unstructured":"Li Z, Oskarsson M, Heyden A (2022) Detailed 3d human body reconstruction from multi-view images combining voxel super-resolution and learned implicit representation. Appl Intell 52(6):6739\u20136759","journal-title":"Appl Intell"},{"issue":"1","key":"6296_CR4","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1186\/s10033-024-00998-7","volume":"37","author":"Q He","year":"2024","unstructured":"He Q, Li L, Li D, Peng T, Zhang X, Cai Y, Zhang X, Tang R (2024) From digital human modeling to human digital twin: framework and perspectives in human factors. Chin J Mech Eng 37(1):9","journal-title":"Chin J Mech Eng"},{"key":"6296_CR5","doi-asserted-by":"crossref","unstructured":"Li X, Li G, Li M, Song H (2024) Parametric body reconstruction based on a single front scan point cloud. IEEE Trans Visual Comput Graph","DOI":"10.1109\/TVCG.2024.3475414"},{"issue":"3\u20134","key":"6296_CR6","first-page":"451","volume":"94","author":"W Feng","year":"2024","unstructured":"Feng W, Li XR, Li X, Li Y, Wen J, Li H, Fang J (2024) The construction of a three-dimensional human body based on semantic-driven parameters to improve virtual fitting. Text Res J 94(3\u20134):451\u2013462","journal-title":"Text Res J"},{"key":"6296_CR7","doi-asserted-by":"crossref","unstructured":"Lyu Z, Fridenfalk M (2024) imetatown: a metaverse system with multiple interactive functions based on virtual reality. IEEE Trans Visual Comput Graph","DOI":"10.1109\/TVCG.2024.3372055"},{"issue":"5","key":"6296_CR8","doi-asserted-by":"publisher","first-page":"3954","DOI":"10.1007\/s10489-024-05330-3","volume":"54","author":"Y Liao","year":"2024","unstructured":"Liao Y, Di Y, Zhu K, Zhou H, Mingyu L, Zhang Y, Duan Q, Liu J (2024) Local feature matching from detector-based to detector-free: a survey. Appl Intell 54(5):3954\u20133989","journal-title":"Appl Intell"},{"issue":"11","key":"6296_CR9","doi-asserted-by":"publisher","first-page":"12569","DOI":"10.1007\/s10489-022-03201-3","volume":"52","author":"X Yue","year":"2022","unstructured":"Yue X, Liu Z, Zhu J, Gao X, Yang B, Tian Y (2022) Coarse-fine point cloud registration based on local point-pair features and the iterative closest point algorithm. Appl Intell 52(11):12569\u201312583","journal-title":"Appl Intell"},{"issue":"1","key":"6296_CR10","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1186\/s42492-023-00145-4","volume":"6","author":"Jiong Yang","year":"2023","unstructured":"Yang Jiong, Zhang Jian, Cai Zhengyang, Fang Dongyang (2023) Novel 3d local feature descriptor of point clouds based on spatial voxel homogenization for feature matching. Vis Comput Ind Biomed Art 6(1):18","journal-title":"Vis Comput Ind Biomed Art"},{"key":"6296_CR11","doi-asserted-by":"publisher","first-page":"104339","DOI":"10.1016\/j.imavis.2021.104339","volume":"117","author":"L Hao","year":"2022","unstructured":"Hao L, Wang H (2022) Geometric feature statistics histogram for both real-valued and binary feature representations of 3d local shape. Image Vis Comput 117:104339","journal-title":"Image Vis Comput"},{"key":"6296_CR12","doi-asserted-by":"crossref","unstructured":"Deng H, Birdal T, Ilic S (2018) Ppf-foldnet: unsupervised learning of rotation invariant 3d local descriptors. In: Proceedings of the European conference on computer vision (ECCV) pp 602\u2013618","DOI":"10.1007\/978-3-030-01228-1_37"},{"key":"6296_CR13","doi-asserted-by":"crossref","unstructured":"Bai X, Luo Z, Zhou L, Fu H, Quan L, Tai C-L (2020) D3feat: joint learning of dense detection and description of 3d local features. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition pp 6359\u20136367","DOI":"10.1109\/CVPR42600.2020.00639"},{"key":"6296_CR14","doi-asserted-by":"crossref","unstructured":"Gojcic Z, Zhou C, Wegner JD, Wieser A (2019) The perfect match: 3d point cloud matching with smoothed densities. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 5545\u20135554","DOI":"10.1109\/CVPR.2019.00569"},{"key":"6296_CR15","doi-asserted-by":"crossref","unstructured":"Choy C, Park J, Koltun V (2019) Fully convolutional geometric features. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 8958\u20138966","DOI":"10.1109\/ICCV.2019.00905"},{"key":"6296_CR16","doi-asserted-by":"crossref","unstructured":"Li L, Zhu S, Fu H, Tan P, Tai C-L (2020) End-to-end learning local multi-view descriptors for 3d point clouds. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition pp 1919\u20131928","DOI":"10.1109\/CVPR42600.2020.00199"},{"issue":"12","key":"6296_CR17","doi-asserted-by":"publisher","first-page":"9687","DOI":"10.1109\/TPAMI.2021.3126713","volume":"44","author":"M Marcon","year":"2021","unstructured":"Marcon M, Spezialetti R, Salti S, Silva L, Di Stefano L (2021) Unsupervised learning of local equivariant descriptors for point clouds. IEEE Trans Pattern Anal Mach Intell 44(12):9687\u20139702","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6296_CR18","doi-asserted-by":"crossref","unstructured":"Wang J, Zhou F, Wen S, Liu X, Lin Y (2017) Deep metric learning with angular loss. In: Proceedings of the IEEE international conference on computer vision pp 2593\u20132601","DOI":"10.1109\/ICCV.2017.283"},{"key":"6296_CR19","doi-asserted-by":"crossref","unstructured":"Wei X, Zhang Y, Gong Y, Zheng N (2018) Kernelized subspace pooling for deep local descriptors. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1867\u20131875","DOI":"10.1109\/CVPR.2018.00200"},{"key":"6296_CR20","doi-asserted-by":"crossref","unstructured":"Luo Z, Shen T, Zhou L, Zhang J, Yao Y, Li S, Fang T, Quan L (2019) Contextdesc: local descriptor augmentation with cross-modality context. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 2527\u20132536","DOI":"10.1109\/CVPR.2019.00263"},{"key":"6296_CR21","doi-asserted-by":"crossref","unstructured":"Huang S, Gojcic Z, Usvyatsov M, Wieser A, Schindler K (2021) Predator: registration of 3d point clouds with low overlap. In: Proceedings of the IEEE\/CVF Conference on computer vision and pattern recognition pp 4267\u20134276","DOI":"10.1109\/CVPR46437.2021.00425"},{"key":"6296_CR22","first-page":"23872","volume":"34","author":"Y Hao","year":"2021","unstructured":"Hao Y, Li F, Saleh M, Busam B, Ilic S (2021) Cofinet: reliable coarse-to-fine correspondences for robust pointcloud registration. Adv Neural Inf Process Syst 34:23872\u201323884","journal-title":"Adv Neural Inf Process Syst"},{"key":"6296_CR23","doi-asserted-by":"crossref","unstructured":"Gojcic Z, Zhou C, Wegner JD, Wieser A (2019) The perfect match: 3d point cloud matching with smoothed densities. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition pp 5545\u20135554","DOI":"10.1109\/CVPR.2019.00569"},{"key":"6296_CR24","doi-asserted-by":"crossref","unstructured":"Qin Z, Yu H, Wang C, Guo Y, Peng Y, Xu K (2022) Geometric transformer for fast and robust point cloud registration. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition pp 11143\u201311152","DOI":"10.1109\/CVPR52688.2022.01086"},{"key":"6296_CR25","doi-asserted-by":"crossref","unstructured":"Sarlin P-E, DeTone D, Malisiewicz T, Rabinovich A (2020) Superglue: learning feature matching with graph neural networks. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition pp 4938\u20134947","DOI":"10.1109\/CVPR42600.2020.00499"},{"key":"6296_CR26","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\/CVF conference on computer vision and pattern recognition, pp 8893\u20138902","DOI":"10.1109\/CVPR46437.2021.00878"},{"issue":"20","key":"6296_CR27","doi-asserted-by":"publisher","first-page":"5119","DOI":"10.3390\/rs14205119","volume":"14","author":"Y Yang","year":"2022","unstructured":"Yang Y, Fang G, Miao Z, Xie Y (2022) Indoor-outdoor point cloud alignment using semantic-geometric descriptor. Remote Sens 14(20):5119","journal-title":"Remote Sens"},{"issue":"8","key":"6296_CR28","doi-asserted-by":"publisher","first-page":"2022","DOI":"10.1109\/TPAMI.2012.257","volume":"35","author":"R Raguram","year":"2012","unstructured":"Raguram R, Chum O, Pollefeys M, Matas J, Frahm J-M (2012) Usac: a universal framework for random sample consensus. IEEE Trans Pattern Anal Mach Intell 35(8):2022\u20132038","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6296_CR29","unstructured":"Ivashechkin M, Bar\u00e1th D, Matas J (2021) Usacv20: robust essential, fundamental and homography matrix estimation. arXiv:2104.05044"},{"issue":"7","key":"6296_CR30","doi-asserted-by":"publisher","first-page":"2209","DOI":"10.1016\/j.patcog.2015.01.020","volume":"48","author":"A Albarelli","year":"2015","unstructured":"Albarelli A, Rodol\u00e0 E, Torsello A (2015) Fast and accurate surface alignment through an isometry-enforcing game. Pattern Recognit 48(7):2209\u20132226","journal-title":"Pattern Recognit"},{"issue":"10","key":"6296_CR31","doi-asserted-by":"publisher","first-page":"7380","DOI":"10.1109\/TGRS.2020.2982221","volume":"58","author":"S Quan","year":"2020","unstructured":"Quan S, Yang J (2020) Compatibility-guided sampling consensus for 3-d point cloud registration. IEEE Trans Geosci Remote Sens 58(10):7380\u20137392","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"6296_CR32","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1016\/j.isprsjprs.2020.07.012","volume":"167","author":"Jiayuan Li","year":"2020","unstructured":"Li Jiayuan, Qingwu Hu, Ai Mingyao (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":"8","key":"6296_CR33","doi-asserted-by":"publisher","first-page":"10376","DOI":"10.1109\/TPAMI.2023.3244951","volume":"45","author":"H Wang","year":"2023","unstructured":"Wang H, Liu Y, Qingyong H, Wang B, Chen J, Dong Z, Guo Y, Wang W, Yang B (2023) Roreg: pairwise point cloud registration with oriented descriptors and local rotations. IEEE Trans Pattern Anal Mach Intell 45(8):10376\u201310393","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6296_CR34","doi-asserted-by":"crossref","unstructured":"Liu Z, Yue X, Zhu J (2024) Sprosac: streamlined progressive sample consensus for coarse-fine point cloud registration. Appl Intell 11\u201319","DOI":"10.1007\/s10489-024-05400-6"},{"key":"6296_CR35","doi-asserted-by":"crossref","unstructured":"Bai X, Luo Z, Zhou L, Chen H, Li L, Hu Z, Fu H, Tai C-L (2021) Pointdsc: robust point cloud registration using deep spatial consistency. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition pp 15859\u201315869","DOI":"10.1109\/CVPR46437.2021.01560"},{"key":"6296_CR36","doi-asserted-by":"crossref","unstructured":"Pais GD, Ramalingam S, Govindu VM, Nascimento JC, Chellappa R, Miraldo P (2020) 3dregnet: a deep neural network for 3d point registration. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition pp 7193\u20137203","DOI":"10.1109\/CVPR42600.2020.00722"},{"key":"6296_CR37","doi-asserted-by":"crossref","unstructured":"Choy C, Dong W, Koltun V (2020) Deep global registration. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition pp 2514\u20132523","DOI":"10.1109\/CVPR42600.2020.00259"},{"key":"6296_CR38","doi-asserted-by":"crossref","unstructured":"Lee J, Kim S, Cho M, Park J (2021) Deep hough voting for robust global registration. In: Proceedings of the IEEE\/CVF international conference on computer vision pp 15994\u201316003","DOI":"10.1109\/ICCV48922.2021.01569"},{"key":"6296_CR39","doi-asserted-by":"crossref","unstructured":"Zhou Q-Y, Park J, Koltun V (2016) Fast global registration. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part II 14. Springer, pp 766\u2013782","DOI":"10.1007\/978-3-319-46475-6_47"},{"key":"6296_CR40","doi-asserted-by":"publisher","first-page":"109274","DOI":"10.1016\/j.measurement.2021.109274","volume":"177","author":"Z Yao","year":"2021","unstructured":"Yao Z, Zhao Q, Li X, Bi Q (2021) Point cloud registration algorithm based on curvature feature similarity. Measurement 177:109274","journal-title":"Measurement"},{"key":"6296_CR41","unstructured":"Liu J, Zhang G, Jia X, Guo H, Li T (2022) Point cloud registration method based on curvature threshold. Laser Optoelectron P 59(18)"},{"issue":"7","key":"6296_CR42","first-page":"990","volume":"35","author":"R Zhang","year":"2023","unstructured":"Zhang R, Sun Z, Jing H, Liu X (2023) Curvature-adaptive deformation graph for 3d point cloud non-rigid registration under multi-geometric constraints. J Comput Aided Des Comput Graph 35(7):990\u2013999","journal-title":"J Comput Aided Des Comput Graph"},{"issue":"4","key":"6296_CR43","doi-asserted-by":"publisher","first-page":"12585","DOI":"10.1109\/LRA.2022.3220148","volume":"7","author":"X Huang","year":"2022","unstructured":"Huang X, Wentao Q, Zuo Y, Fang Y, Zhao X (2022) Gmf: general multimodal fusion framework for correspondence outlier rejection. IEEE Robot Autom Lett 7(4):12585\u201312592","journal-title":"IEEE Robot Autom Lett"},{"key":"6296_CR44","doi-asserted-by":"crossref","unstructured":"Li X, Yan Z, Lin S, Jia D (2020) Point cloud registration based on neighborhood characteristic point extraction and matching. Acta Photonica Sinica 49(4)","DOI":"10.3788\/gzxb20204904.0415001"},{"issue":"1\u20132","key":"6296_CR45","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1177\/0020294019878869","volume":"53","author":"Ls Wu","year":"2020","unstructured":"Wu Ls, Wang Gl, Hu Y (2020) Iterative closest point registration for fast point feature histogram features of a volume density optimization algorithm. Meas Control 53(1\u20132):29\u201339","journal-title":"Meas Control"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-025-06296-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-025-06296-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-025-06296-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T05:08:43Z","timestamp":1757135323000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-025-06296-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,29]]},"references-count":45,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["6296"],"URL":"https:\/\/doi.org\/10.1007\/s10489-025-06296-6","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,29]]},"assertion":[{"value":"12 January 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 January 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"386"}}