{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:14:11Z","timestamp":1767323651581,"version":"3.48.0"},"publisher-location":"Singapore","reference-count":35,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819557363","type":"print"},{"value":"9789819557370","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-5737-0_27","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:09:29Z","timestamp":1767323369000},"page":"382-395","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Automatic Robotic High-Precision 3D Modeling System Based on\u00a0Active Speckle-Assisted Multi-view Registration and\u00a0Global Optimization"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7191-2782","authenticated-orcid":false,"given":"Hongchao","family":"Song","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Nie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Biao","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"key":"27_CR1","doi-asserted-by":"crossref","unstructured":"Ao, S., Hu, Q., Wang, H., Xu, K., Guo, Y.: Buffer: balancing accuracy, efficiency, and generalizability in point cloud registration. In: 2023 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1255\u20131264. Vancouver, BC, Canada (2023)","DOI":"10.1109\/CVPR52729.2023.00127"},{"key":"27_CR2","doi-asserted-by":"crossref","unstructured":"Bai, X., Luo, Z., Zhou, L., Fu, H., Quan, L., Tai, C.L.: D3Feat: joint learning of dense detection and description of 3D local features. In: 2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6358\u20136366. Seattle, WA, USA (2020)","DOI":"10.1109\/CVPR42600.2020.00639"},{"key":"27_CR3","doi-asserted-by":"crossref","unstructured":"Banani, M.E., et al.: Self-supervised correspondence estimation via multiview registration. In: 2023 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 1216\u20131225. Waikoloa, HI, USA (2023)","DOI":"10.1109\/WACV56688.2023.00127"},{"key":"27_CR4","doi-asserted-by":"crossref","unstructured":"Boroson, E.R., Hewitt, R., Ayanian, N., de\u00a0la Croix, J.P.: Inter-robot range measurements in pose graph optimization. In: 2020 IEEE\/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 4806\u20134813. Las Vegas, NV, USA (2020)","DOI":"10.1109\/IROS45743.2020.9341227"},{"key":"27_CR5","doi-asserted-by":"crossref","unstructured":"Cao, Y., Shi, Y., Cheng, Z., Li, H.: End-to-End point cloud registration via rotation equivariant descriptors. In: 2023 IEEE\/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 5804\u20135811. Detroit, MI, USA (2023)","DOI":"10.1109\/IROS55552.2023.10342154"},{"key":"27_CR6","doi-asserted-by":"crossref","unstructured":"Cheng, R., Papozov, C., Helmick, D., Tjersland, M.: A direct semi-exhaustive search method for robust, partial-to-full point cloud registration. In: 2024 IEEE\/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 7521\u20137527. Abu Dhabi, United Arab Emirates (2024)","DOI":"10.1109\/IROS58592.2024.10801518"},{"key":"27_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIM.2024.3470008","volume":"73","author":"YQ Cheng","year":"2024","unstructured":"Cheng, Y.Q., Li, W.L., Jiang, C., Wang, D.F., Xing, H.W., Xu, W.: MVGR: Mean-Variance minimization Global Registration method for multiview point cloud in robot inspection. IEEE Trans. Instrum. Meas. 73, 1\u201315 (2024)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"27_CR8","doi-asserted-by":"crossref","unstructured":"Choi, S., Zhou, Q.Y., Koltun, V.: Robust reconstruction of indoor scenes. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5556\u20135565. Boston, MA, USA (2015)","DOI":"10.1109\/CVPR.2015.7299195"},{"key":"27_CR9","unstructured":"Csardi, G., Nepusz, T.: The IGraph software package for complex network research. InterJournal Complex Syst. 5, 1\u20139 (2006). http:\/\/igraph.org\/"},{"key":"27_CR10","doi-asserted-by":"crossref","unstructured":"DeTone, D., Malisiewicz, T., Rabinovich, A.: SuperPoint: self-supervised interest point detection and description. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). Salt Lake City, UT, USA (2018)","DOI":"10.1109\/CVPRW.2018.00060"},{"key":"27_CR11","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1016\/j.isprsjprs.2020.03.013","volume":"163","author":"Z Dong","year":"2020","unstructured":"Dong, Z., et al.: Registration of large-scale terrestrial laser scanner point clouds: a review and benchmark. ISPRS J. Photogrammetry Remote Sens. 163, 327\u2013342 (2020)","journal-title":"ISPRS J. Photogrammetry Remote Sens."},{"key":"27_CR12","doi-asserted-by":"crossref","unstructured":"Du, X., et al.: OBHMR: robust partial-to-full generalized point set registration with overlap-guided bidirectional hybrid mixture model. In: 2024 IEEE\/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 7235\u20137242. Abu Dhabi, United Arab Emirates (2024)","DOI":"10.1109\/IROS58592.2024.10801428"},{"key":"27_CR13","doi-asserted-by":"crossref","unstructured":"Gojcic, Z., Zhou, C., Wegner, J.D., Guibas, L.J., Birdal, T.: Learning multiview 3D point cloud registration. In: 2020 IEEE Computer Vision and Pattern Recognition (CVPR), pp. 1756\u20131766. Seattle, WA, USA (2020)","DOI":"10.1109\/CVPR42600.2020.00183"},{"issue":"12","key":"27_CR14","doi-asserted-by":"publisher","first-page":"4338","DOI":"10.1109\/TPAMI.2020.3005434","volume":"43","author":"Y Guo","year":"2021","unstructured":"Guo, Y., Wang, H., Hu, Q., Liu, H., Liu, L., Bennamoun, M.: Deep learning for 3D point clouds: a survey. IEEE Trans. Pattern Anal. Mach. Intell. 43(12), 4338\u20134364 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"27_CR15","doi-asserted-by":"crossref","unstructured":"Huang, X., Mei, G., Zhang, J.: Feature-metric registration: a fast semi-supervised approach for robust point cloud registration without correspondences. In: 2020 IEEE Computer Vision and Pattern Recognition (CVPR), pp. 11363\u201311371. Seattle, WA, USA (2020)","DOI":"10.1109\/CVPR42600.2020.01138"},{"key":"27_CR16","doi-asserted-by":"crossref","unstructured":"Jiang, H., Dang, Z., Wei, Z., Xie, J., Yang, J., Salzmann, M.: Robust outlier rejection for 3D registration with variational bayes. In: 2023 IEEE Computer Vision and Pattern Recognition (CVPR), pp. 1148\u20131157. Vancouver, BC, Canada (2023)","DOI":"10.1109\/CVPR52729.2023.00117"},{"key":"27_CR17","doi-asserted-by":"publisher","unstructured":"Li, F., Li, T., Zhou, S., Lin, Y.: Robust multiview point cloud registration using algebraic connectivity and spatial compatibility. IEEE Geosci. Remote Sens. Lett. (2024). https:\/\/doi.org\/10.1109\/TGRS.2024.3515203","DOI":"10.1109\/TGRS.2024.3515203"},{"key":"27_CR18","doi-asserted-by":"crossref","unstructured":"Li, L., Zhu, S., Fu, H., Tan, P., Tai, C.L.: End-to-end learning local multi-view descriptors for 3D point clouds. In: 2020 IEEE Computer Vision and Pattern Recognition (CVPR), pp. 1916\u20131925. Seattle, WA, USA (2020)","DOI":"10.1109\/CVPR42600.2020.00199"},{"issue":"11","key":"27_CR19","doi-asserted-by":"publisher","first-page":"9319","DOI":"10.1109\/LRA.2024.3455783","volume":"9","author":"S Li","year":"2024","unstructured":"Li, S., Zhu, J., Xie, Y., Hu, N., Wang, D.: Matching distance and geometric distribution aided learning multiview point cloud registration. IEEE Trans. Robot. Automat. Lett. 9(11), 9319\u20139326 (2024)","journal-title":"IEEE Trans. Robot. Automat. Lett."},{"key":"27_CR20","doi-asserted-by":"crossref","unstructured":"Li, Y., Harada, T.: LEPARD: learning partial point cloud matching in rigid and deformable scenes. In: 2022 IEEE Computer Vision and Pattern Recognition (CVPR). New Orleans, LA, USA (2022)","DOI":"10.1109\/CVPR52688.2022.00547"},{"key":"27_CR21","doi-asserted-by":"crossref","unstructured":"Lindenberger, P., Sarlin, P.E., Pollefeys, M.: LightGlue: local feature matching at light speed. In: 2023 IEEE International Conference on Computer Vision (ICCV), pp. 17581\u201317592. Paris, France (2023)","DOI":"10.1109\/ICCV51070.2023.01616"},{"key":"27_CR22","doi-asserted-by":"crossref","unstructured":"Liu, Z., Wang, X., Pu, B., Tang, J., Sun, J.: Wireframepose: Monocular 6-D pose estimation of metal parts based on wireframe extraction and matching. IEEE Trans. Instrum. Meas. 73, 1\u201310 (2024)","DOI":"10.1109\/TIM.2024.3460945"},{"key":"27_CR23","doi-asserted-by":"crossref","unstructured":"Qiao, Z., Yu, Z., Yin, H., Shen, S.: Pyramid semantic graph-based global point cloud registration with low overlap. In: 2023 IEEE\/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 11202\u201311209. Detroit, MI, USA (2023)","DOI":"10.1109\/IROS55552.2023.10341394"},{"key":"27_CR24","doi-asserted-by":"crossref","unstructured":"Qin, Z., Yu, H., Wang, C., Guo, Y., Peng, Y., Xu, K.: Geometric transformer for fast and robust point cloud registration. In: 2022 IEEE Computer Vision and Pattern Recognition (CVPR), pp. 11133\u201311142. New Orleans, LA, USA (2022)","DOI":"10.1109\/CVPR52688.2022.01086"},{"issue":"11","key":"27_CR25","doi-asserted-by":"publisher","first-page":"18379","DOI":"10.1364\/OE.492045","volume":"31","author":"J Sun","year":"2023","unstructured":"Sun, J., Yang, Z., Li, F., Hao, Q., Zhang, S.: Projected feature assisted coarse to fine point cloud registration method for large-size 3D measurement. Opt. Express 31(11), 18379\u201318398 (2023)","journal-title":"Opt. Express"},{"key":"27_CR26","doi-asserted-by":"crossref","unstructured":"Wang, H., et al.: Robust multiview point cloud registration with reliable pose graph initialization and history reweighting. In: 2023 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9506\u20139515. Vancouver, BC, Canada (2023)","DOI":"10.1109\/CVPR52729.2023.00917"},{"key":"27_CR27","doi-asserted-by":"crossref","unstructured":"Wang, H., Liu, Y., Dong, Z., Wang, W.: You only hypothesize once: point cloud registration with rotation-equivariant descriptors. In: Proceedings of the 30th ACM International Conference on Multimedia, pp. 1630\u20131641. New York, NY, USA (2022)","DOI":"10.1145\/3503161.3548023"},{"issue":"8","key":"27_CR28","doi-asserted-by":"publisher","first-page":"10376","DOI":"10.1109\/TPAMI.2023.3244951","volume":"45","author":"H Wang","year":"2023","unstructured":"Wang, H., et al.: ROREG: pairwise point cloud registration with oriented descriptors and local rotations. IEEE Trans. Pattern Anal. Mach. Intell. 45(8), 10376\u201310393 (2023)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"27_CR29","doi-asserted-by":"crossref","unstructured":"Wu, Q., et al.: SGNet: salient geometric network for point cloud registration. In: 2024 IEEE\/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 3276\u20133282. Abu Dhabi, United Arab Emirates (2024)","DOI":"10.1109\/IROS58592.2024.10802262"},{"key":"27_CR30","doi-asserted-by":"crossref","unstructured":"Wu, Q., et al.: Graph matching optimization network for point cloud registration. In: 2023 IEEE\/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 5320\u20135325. Detroit, MI, USA (2023)","DOI":"10.1109\/IROS55552.2023.10342346"},{"key":"27_CR31","doi-asserted-by":"crossref","unstructured":"Zhang, X., Yang, J., Zhang, S., Zhang, Y.: 3D registration with maximal cliques. In: 2023 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 17745\u201317754. Vancouver, BC, Canada (2023)","DOI":"10.1109\/CVPR52729.2023.01702"},{"key":"27_CR32","doi-asserted-by":"crossref","unstructured":"Zhao, G., Guo, Z., Ma, H.: SGOR: outlier removal by leveraging semantic and geometric information for robust point cloud registration. In: 2024 IEEE\/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 9388\u20139395. Abu Dhabi, United Arab Emirates (2024)","DOI":"10.1109\/IROS58592.2024.10801642"},{"key":"27_CR33","unstructured":"Zhao, J., Zhu, Q., Wang, Y., Peng, W., Zhang, H., Mao, J.: Registration of multiview point clouds with unknown overlap. IEEE Trans. Multimedia, 1\u201316 (2023)"},{"key":"27_CR34","doi-asserted-by":"crossref","unstructured":"Zhou, L., Wu, G., Zuo, Y., Chen, X., Hu, H.: A comprehensive review of vision-based 3D reconstruction methods. Sensors 24(7) (2024)","DOI":"10.3390\/s24072314"},{"key":"27_CR35","unstructured":"Zhou, Q.Y., Park, J., Koltun, V.: Open3D: a modern library for 3D data processing. arXiv:1801.09847 (2018)"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5737-0_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:09:32Z","timestamp":1767323372000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5737-0_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819557363","9789819557370"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5737-0_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2025.prcv.cn\/index.asp","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}