{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T15:09:39Z","timestamp":1778252979584,"version":"3.51.4"},"reference-count":54,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100013061","name":"Jilin Scientific and Technological Development Program","doi-asserted-by":"publisher","award":["20240302033GX"],"award-info":[{"award-number":["20240302033GX"]}],"id":[{"id":"10.13039\/501100013061","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Displays"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.displa.2026.103430","type":"journal-article","created":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T22:56:18Z","timestamp":1773615378000},"page":"103430","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["GCG-PROSAC: a geometric consistency-based robust estimation algorithm for accelerated 3D point cloud registration"],"prefix":"10.1016","volume":"93","author":[{"given":"Zeyuan","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaofeng","family":"Yue","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.displa.2026.103430_b0005","doi-asserted-by":"crossref","DOI":"10.1007\/s00371-025-03896-8","article-title":"PCR-PoseNet: a 6D pose estimation method for texture-less and highly reflective industrial parts with point cloud shape recovery","author":"Han","year":"2025","journal-title":"Visual Comput"},{"key":"10.1016\/j.displa.2026.103430_b0010","article-title":"Excavator 3D pose estimation from point cloud with self-supervised deep learning","author":"Zhang","year":"2025","journal-title":"Comput. Aided Civ. Inf. Eng."},{"key":"10.1016\/j.displa.2026.103430_b0015","doi-asserted-by":"crossref","DOI":"10.1002\/rob.22571","article-title":"A robust pose estimation method for robot grasping in bin-picking scenarios using point cloud","author":"Lu","year":"2025","journal-title":"J. Field Rob."},{"key":"10.1016\/j.displa.2026.103430_b0020","article-title":"One-nearest neighborhood guides inlier estimation for unsupervised point cloud registration","author":"Yuan","year":"2024","journal-title":"IEEE Trans. Neural Networks Learn. Syst."},{"issue":"6","key":"10.1016\/j.displa.2026.103430_b0025","doi-asserted-by":"crossref","first-page":"5117","DOI":"10.1007\/s10489-024-05400-6","article-title":"SPROSAC: streamlined progressive sample consensus for coarse-fine point cloud registration","volume":"54","author":"Liu","year":"2024","journal-title":"Appl. Intell."},{"issue":"9","key":"10.1016\/j.displa.2026.103430_b0030","doi-asserted-by":"crossref","first-page":"11136","DOI":"10.1109\/TPAMI.2023.3262780","article-title":"QGORE: quadratic-time guaranteed outlier removal for point cloud registration","volume":"45","author":"Li","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"7","key":"10.1016\/j.displa.2026.103430_b0035","first-page":"7986","article-title":"A new outlier removal strategy based on reliability of correspondence graph for fast point cloud registration","volume":"45","author":"Yan","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"9","key":"10.1016\/j.displa.2026.103430_b0040","doi-asserted-by":"crossref","first-page":"6222","DOI":"10.1109\/TVCG.2023.3329578","article-title":"EGST: Enhanced geometric structure transformer for point cloud registration","volume":"30","author":"Yuan","year":"2023","journal-title":"IEEE Trans. Visual Comput. Graphics"},{"key":"10.1016\/j.displa.2026.103430_b0045","doi-asserted-by":"crossref","unstructured":"Yuan Y, Wu Y, Fan X, Gong M, Miao Q, Ma W (2025) Where Precision Meets Efficiency: Transformation Diffusion Model for Point Cloud Registration, in Proceedings of the AAAI Conference on Artificial Intelligence, (Vol. 39, pp. 9734-9742).","DOI":"10.1609\/aaai.v39i9.33055"},{"issue":"6","key":"10.1016\/j.displa.2026.103430_b0050","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1145\/358669.358692","article-title":"Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography","volume":"24","author":"Fischler","year":"1981","journal-title":"Commun. ACM"},{"key":"10.1016\/j.displa.2026.103430_b0055","doi-asserted-by":"crossref","unstructured":"Barath D, Matas J (2018) Graph-cut RANSAC, in Proceedings of the IEEE conference on computer vision and pattern recognition, (pp. 6733-6741).","DOI":"10.1109\/CVPR.2018.00704"},{"key":"10.1016\/j.displa.2026.103430_b0060","doi-asserted-by":"crossref","unstructured":"Barath D, Matas J, Noskova J (2019) MAGSAC: marginalizing sample consensus, in Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, (pp. 10197-10205).","DOI":"10.1109\/CVPR.2019.01044"},{"key":"10.1016\/j.displa.2026.103430_b0065","unstructured":"Ivashechkin M, Barath D, Matas J (2021) USACv20: robust essential, fundamental and homography matrix estimation. arXiv preprint arXiv:2104.05044."},{"key":"10.1016\/j.displa.2026.103430_b0070","unstructured":"Torr PH, Nasuto SJ, Bishop JM (2002) Napsac: High noise, high dimensional robust estimation-it\u2019s in the bag, in British Machine Vision Conference (BMVC), (Vol. 2, pp. 3)."},{"key":"10.1016\/j.displa.2026.103430_b0075","doi-asserted-by":"crossref","unstructured":"Chum O, Matas J (2005) Matching with PROSAC-progressive sample consensus, in 2005 IEEE computer society conference on computer vision and pattern recognition (CVPR'05), (Vol. 1, pp. 220-226). IEEE.","DOI":"10.1109\/CVPR.2005.221"},{"issue":"10","key":"10.1016\/j.displa.2026.103430_b0080","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.1109\/TPAMI.2005.199","article-title":"Guided-MLESAC: faster image transform estimation by using matching priors","volume":"27","author":"Tordoff","year":"2005","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.displa.2026.103430_b0085","doi-asserted-by":"crossref","unstructured":"Chum O, Matas J, Kittler J (2003) Locally optimized RANSAC, in Pattern Recognition: 25th DAGM Symposium, Magdeburg, Germany, September 10-12, 2003. Proceedings 25, (pp. 236-243). Springer.","DOI":"10.1007\/978-3-540-45243-0_31"},{"key":"10.1016\/j.displa.2026.103430_b0090","doi-asserted-by":"crossref","unstructured":"Lebeda K, Matas J, Chum O (2012) Fixing the locally optimized ransac\u2013full experimental evaluation, in British machine vision conference, (Vol. 2). Citeseer.","DOI":"10.5244\/C.26.95"},{"key":"10.1016\/j.displa.2026.103430_b0095","series-title":"2013 IEEE International Conference on Robotics and Automation","first-page":"2080","article-title":"Pose estimation using local structure-specific shape and appearance context","author":"Buch","year":"2013"},{"issue":"8","key":"10.1016\/j.displa.2026.103430_b0100","doi-asserted-by":"crossref","first-page":"5908","DOI":"10.1109\/TGRS.2020.2972982","article-title":"Robust geometric model estimation based on scaled Welsch q-norm","volume":"58","author":"Li","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"10","key":"10.1016\/j.displa.2026.103430_b0105","doi-asserted-by":"crossref","first-page":"837","DOI":"10.1016\/j.imavis.2004.02.009","article-title":"Randomized RANSAC with Td, d test","volume":"22","author":"Matas","year":"2004","journal-title":"Image Vis. Comput."},{"key":"10.1016\/j.displa.2026.103430_b0110","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"1304","article-title":"MAGSAC++, a fast, reliable and accurate robust estimator","author":"Barath","year":"2020"},{"issue":"12","key":"10.1016\/j.displa.2026.103430_b0115","doi-asserted-by":"crossref","first-page":"2868","DOI":"10.1109\/TPAMI.2017.2773482","article-title":"Guaranteed outlier removal for point cloud registration with correspondences","volume":"40","author":"Bustos","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.displa.2026.103430_b0120","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"11632","article-title":"Pvn3d: a deep point-wise 3d keypoints voting network for 6dof pose estimation","author":"He","year":"2020"},{"key":"10.1016\/j.displa.2026.103430_b0125","series-title":"2009 IEEE 12th international conference on computer vision workshops, ICCV Workshops","first-page":"689","article-title":"Intrinsic shape signatures: a shape descriptor for 3D object recognition","author":"Zhong","year":"2009"},{"key":"10.1016\/j.displa.2026.103430_b0130","unstructured":"Steder B, Rusu RB, Konolige K, Burgard W (2010) NARF: 3D range image features for object recognition, in Workshop on Defining and Solving Realistic Perception Problems in Personal Robotics at the IEEE\/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), (Vol. 44, pp. 2). Citeseer."},{"issue":"2\u20133","key":"10.1016\/j.displa.2026.103430_b0135","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1007\/s11263-009-0296-z","article-title":"On the repeatability and quality of keypoints for local feature-based 3D object retrieval from cluttered scenes","volume":"89","author":"Mian","year":"2010","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.displa.2026.103430_b0140","unstructured":"Suwajanakorn S, Snavely N, Tompson JJ, Norouzi M (2018) Discovery of latent 3d keypoints via end-to-end geometric reasoning. Advances in neural information processing systems 31."},{"issue":"2","key":"10.1016\/j.displa.2026.103430_b0145","doi-asserted-by":"crossref","first-page":"5437","DOI":"10.1109\/LRA.2022.3157438","article-title":"SKP: semantic 3D keypoint detection for category-level robotic manipulation","volume":"7","author":"Luo","year":"2022","journal-title":"IEEE Rob. Autom. Lett."},{"key":"10.1016\/j.displa.2026.103430_b0150","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.neucom.2023.127171","article-title":"KPDet: keypoint-based 3D object detection with parametric radius learning","volume":"572","author":"Huang","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.displa.2026.103430_b0155","series-title":"2010 IEEE computer society conference on computer vision and pattern recognition","first-page":"998","article-title":"Model globally, match locally: Efficient and robust 3D object recognition","author":"Drost","year":"2010"},{"key":"10.1016\/j.displa.2026.103430_b0160","series-title":"2009 IEEE international conference on robotics and automation","first-page":"3212","article-title":"Fast point feature histograms (FPFH) for 3D registration","author":"Rusu","year":"2009"},{"issue":"11","key":"10.1016\/j.displa.2026.103430_b0165","doi-asserted-by":"crossref","first-page":"12569","DOI":"10.1007\/s10489-022-03201-3","article-title":"Coarse-fine point cloud registration based on local point-pair features and the iterative closest point algorithm","volume":"52","author":"Yue","year":"2022","journal-title":"Appl. Intell."},{"key":"10.1016\/j.displa.2026.103430_b0170","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"6359","article-title":"D3feat: joint learning of dense detection and description of 3d local features","author":"Bai","year":"2020"},{"key":"10.1016\/j.displa.2026.103430_b0175","doi-asserted-by":"crossref","DOI":"10.1109\/TCSVT.2023.3270315","article-title":"Task-oriented compact representation of 3D point clouds via a matrix optimization-driven network","author":"Qian","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.displa.2026.103430_b0180","doi-asserted-by":"crossref","unstructured":"Ren DY, Li JW, Wu ZY, Guo J, Wei MQ, Guo YW (2023) MFFNet: multimodal feature fusion network for point cloud semantic segmentation. Visual Comput.:13. 10.1007\/s00371-023-02907-w.","DOI":"10.1007\/s00371-023-02907-w"},{"key":"10.1016\/j.displa.2026.103430_b0185","unstructured":"Tian C, Li Z, Yuan H, Hamzaoui R, Shen L, Kwong S (2024) Feature Compression for Cloud-Edge Multimodal 3D Object Detection."},{"key":"10.1016\/j.displa.2026.103430_b0190","doi-asserted-by":"crossref","unstructured":"Muja M, Lowe DG (2009) Fast approximate nearest neighbors with automatic algorithm configuration. VISAPP (1) 2(331-340):2.","DOI":"10.5220\/0001787803310340"},{"issue":"5","key":"10.1016\/j.displa.2026.103430_b0195","first-page":"6183","article-title":"Robust point cloud registration framework based on deep graph matching","volume":"45","author":"Fu","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"1","key":"10.1016\/j.displa.2026.103430_b0200","doi-asserted-by":"crossref","first-page":"1135","DOI":"10.1109\/TPAMI.2022.3148308","article-title":"STORM: structure-based overlap matching for partial point cloud registration","volume":"45","author":"Wang","year":"2023","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.displa.2026.103430_b0205","unstructured":"Barath D, Ivashechkin M, Matas J (2019) Progressive NAPSAC: sampling from gradually growing neighborhoods. arXiv preprint arXiv:1906.02295."},{"key":"10.1016\/j.displa.2026.103430_b0210","doi-asserted-by":"crossref","unstructured":"Ivashechkin M, Barath D, Matas J (2021) Vsac: Efficient and accurate estimator for h and f, in Proceedings of the IEEE\/CVF international conference on computer vision, (pp. 15243-15252).","DOI":"10.1109\/ICCV48922.2021.01496"},{"key":"10.1016\/j.displa.2026.103430_b0215","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1016\/j.isprsjprs.2020.07.012","article-title":"GESAC: robust graph enhanced sample consensus for point cloud registration","volume":"167","author":"Li","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"issue":"1","key":"10.1016\/j.displa.2026.103430_b0220","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1006\/cviu.1999.0832","article-title":"MLESAC: a new robust estimator with application to estimating image geometry","volume":"78","author":"Torr","year":"2000","journal-title":"Comput. Vis. Image Underst."},{"key":"10.1016\/j.displa.2026.103430_b0225","doi-asserted-by":"crossref","unstructured":"Sattler T, Leibe B, Kobbelt L (2009) SCRAMSAC: Improving RANSAC's efficiency with a spatial consistency filter, in 2009 IEEE 12th International Conference on Computer Vision, (pp. 2090-2097). IEEE.","DOI":"10.1109\/ICCV.2009.5459459"},{"key":"10.1016\/j.displa.2026.103430_b0230","unstructured":"Choi J, Medioni G (2009) StaRSaC: Stable random sample consensus for parameter estimation."},{"issue":"8","key":"10.1016\/j.displa.2026.103430_b0235","doi-asserted-by":"crossref","first-page":"2022","DOI":"10.1109\/TPAMI.2012.257","article-title":"USAC: a universal framework for random sample consensus","volume":"35","author":"Raguram","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.displa.2026.103430_b0240","doi-asserted-by":"crossref","unstructured":"Boykov YY, Jolly M-P (2001). Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images. in 8th IEEE International Conference on Computer Vision (ICCV2001), vol.1, Vancouver, British Columbia, Canada.","DOI":"10.1109\/ICCV.2001.937505"},{"key":"10.1016\/j.displa.2026.103430_b0245","doi-asserted-by":"crossref","unstructured":"Tombari F, Salti S, Di Stefano L (2010) Unique shape context for 3D data description, in Proceedings of the ACM workshop on 3D object retrieval, (pp. 57-62).","DOI":"10.1145\/1877808.1877821"},{"issue":"1","key":"10.1016\/j.displa.2026.103430_b0250","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1007\/s11263-012-0545-4","article-title":"Performance evaluation of 3D keypoint detectors","volume":"102","author":"Tombari","year":"2013","journal-title":"Int. J. Comput. Vis."},{"issue":"10","key":"10.1016\/j.displa.2026.103430_b0255","doi-asserted-by":"crossref","first-page":"1584","DOI":"10.1109\/TPAMI.2006.213","article-title":"Three-dimensional model-based object recognition and segmentation in cluttered scenes","volume":"28","author":"Mian","year":"2006","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.displa.2026.103430_b0260","series-title":"2021 IEEE International Conference on Robotics and Automation (ICRA)","first-page":"13828","article-title":"Clipper: A graph-theoretic framework for robust data association","author":"Lusk","year":"2021"},{"key":"10.1016\/j.displa.2026.103430_b0265","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"1802","article-title":"3dmatch: learning local geometric descriptors from rgb-d reconstructions","author":"Zeng","year":"2017"},{"key":"10.1016\/j.displa.2026.103430_b0270","series-title":"Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques","first-page":"303","article-title":"A volumetric method for building complex models from range images","author":"Curless","year":"1996"}],"container-title":["Displays"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0141938226000934?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0141938226000934?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T14:12:13Z","timestamp":1778249533000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0141938226000934"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":54,"alternative-id":["S0141938226000934"],"URL":"https:\/\/doi.org\/10.1016\/j.displa.2026.103430","relation":{},"ISSN":["0141-9382"],"issn-type":[{"value":"0141-9382","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"GCG-PROSAC: a geometric consistency-based robust estimation algorithm for accelerated 3D point cloud registration","name":"articletitle","label":"Article Title"},{"value":"Displays","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.displa.2026.103430","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"103430"}}