{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T20:45:59Z","timestamp":1773693959019,"version":"3.50.1"},"reference-count":71,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T00:00:00Z","timestamp":1620691200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002920","name":"Research Grants Council, University Grants Committee","doi-asserted-by":"publisher","award":["17200218"],"award-info":[{"award-number":["17200218"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002920","name":"Research Grants Council, University Grants Committee","doi-asserted-by":"publisher","award":["27200520"],"award-info":[{"award-number":["27200520"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Coarse registration of 3D point clouds plays an indispensable role for parametric, semantically rich, and realistic digital twin buildings (DTBs) in the practice of GIScience, manufacturing, robotics, architecture, engineering, and construction. However, the existing methods have prominently been challenged by (i) the high cost of data collection for numerous existing buildings and (ii) the computational complexity from self-similar layout patterns. This paper studies the registration of two low-cost data sets, i.e., colorful 3D point clouds captured by smartphones and 2D CAD drawings, for resolving the first challenge. We propose a novel method named \u2018Registration based on Architectural Reflection Detection\u2019 (RegARD) for transforming the self-symmetries in the second challenge from a barrier of coarse registration to a facilitator. First, RegARD detects the innate architectural reflection symmetries to constrain the rotations and reduce degrees of freedom. Then, a nonlinear optimization formulation together with advanced optimization algorithms can overcome the second challenge. As a result, high-quality coarse registration and subsequent low-cost DTBs can be created with semantic components and realistic appearances. Experiments showed that the proposed method outperformed existing methods considerably in both effectiveness and efficiency, i.e., 49.88% less error and 73.13% less time, on average. The RegARD presented in this paper first contributes to coarse registration theories and exploitation of symmetries and textures in 3D point clouds and 2D CAD drawings. For practitioners in the industries, RegARD offers a new automatic solution to utilize ubiquitous smartphone sensors for massive low-cost DTBs.<\/jats:p>","DOI":"10.3390\/rs13101882","type":"journal-article","created":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T11:30:16Z","timestamp":1620732616000},"page":"1882","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["RegARD: Symmetry-Based Coarse Registration of Smartphone\u2019s Colorful Point Clouds with CAD Drawings for Low-Cost Digital Twin Buildings"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1441-1583","authenticated-orcid":false,"given":"Yijie","family":"Wu","sequence":"first","affiliation":[{"name":"Department of Real Estate and Construction, The University of Hong Kong, Pokfulam, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7571-8015","authenticated-orcid":false,"given":"Jianga","family":"Shang","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2217-3693","authenticated-orcid":false,"given":"Fan","family":"Xue","sequence":"additional","affiliation":[{"name":"Department of Real Estate and Construction, The University of Hong Kong, Pokfulam, Hong Kong, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,11]]},"reference":[{"key":"ref_1","unstructured":"Xue, F., Chiaradia, A., Webster, C.J., Liu, D., Xu, J., and Lu, W. (2018, January 24\u201327). Personalized walkability assessment for pedestrian paths: An as-built BIM approach using ubiquitous augmented reality (AR) smartphone and deep transfer learning. Proceedings of the 23rd International Symposium on the Advancement of Construction Management and Real Estate, Guiyang, China."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"992","DOI":"10.1109\/LGRS.2016.2558486","article-title":"An indoor backpack system for 2-D and 3-D mapping of building interiors","volume":"13","author":"Wen","year":"2016","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1313","DOI":"10.1007\/s10845-019-01512-w","article-title":"A state-of-the-art survey of Digital Twin: Techniques, engineering product lifecycle management and business innovation perspectives","volume":"31","author":"Lim","year":"2019","journal-title":"J. Intell. Manuf."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"147406","DOI":"10.1109\/ACCESS.2019.2946515","article-title":"Digital twin: Vision, benefits, boundaries, and creation for buildings","volume":"7","author":"Khajavi","year":"2019","journal-title":"IEEE Access"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1016\/j.isprsjprs.2020.07.020","article-title":"From LiDAR point cloud towards digital twin city: Clustering city objects based on Gestalt principles","volume":"167","author":"Xue","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Bianchini, C., and Nicastro, S. (2018, January 26\u201330). From BIM to H-BIM. Proceedings of the 2018 3rd Digital Heritage International Congress (DigitalHERITAGE) Held Jointly with 2018 24th International Conference on Virtual Systems & Multimedia (VSMM 2018), San Francisco, CA, USA.","DOI":"10.1109\/DigitalHeritage.2018.8810087"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2067","DOI":"10.3390\/heritage2030125","article-title":"Informative Models for Architectural Heritage","volume":"2","author":"Attenni","year":"2019","journal-title":"Heritage"},{"key":"ref_8","unstructured":"NIC (2021, May 10). Data for the Public Good. Available online: https:\/\/nic.org.uk\/app\/uploads\/Data-for-the-Public-Good-NIC-Report.pdf."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Xue, F., Guo, H., and Lu, W. (2020, January 2\u20134). Digital twinning of construction objects: Lessons learned from pose estimation methods. Proceedings of the 37th Information Technology for Construction Conference (CIB W78), S\u00e3o Paulo, Brazil.","DOI":"10.46421\/2706-6568.37.2020.paper023"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"04019024","DOI":"10.1061\/(ASCE)CP.1943-5487.0000839","article-title":"From semantic segmentation to semantic registration: Derivative-Free Optimization\u2013based approach for automatic generation of semantically rich as-built Building Information Models from 3D point clouds","volume":"33","author":"Xue","year":"2019","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"103183","DOI":"10.1016\/j.autcon.2020.103183","article-title":"Semi-automatic geometric digital twinning for existing buildings based on images and CAD drawings","volume":"115","author":"Lu","year":"2020","journal-title":"Autom. Constr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"103179","DOI":"10.1016\/j.autcon.2020.103179","article-title":"Towards a semantic Construction Digital Twin: Directions for future research","volume":"114","author":"Boje","year":"2020","journal-title":"Autom. Constr."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"101245","DOI":"10.1016\/j.aei.2020.101245","article-title":"Semantic enrichment of building and city information models: A ten-year review","volume":"47","author":"Xue","year":"2021","journal-title":"Adv. Eng. Inform."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1842","DOI":"10.1109\/LGRS.2018.2866280","article-title":"Hand-held 3-D reconstruction of large-scale scene with kinect sensors based on surfel and video sequences","volume":"15","author":"Xu","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.autcon.2018.01.014","article-title":"4-Plane congruent sets for automatic registration of as-is 3D point clouds with 3D BIM models","volume":"89","author":"Bueno","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1109\/TRO.2013.2279412","article-title":"3-D mapping with an RGB-D camera","volume":"30","author":"Endres","year":"2013","journal-title":"IEEE Trans. Robot."},{"key":"ref_17","unstructured":"Linowes, J., and Babilinski, K. (2017). Augmented Reality for Developers: Build Practical Augmented Reality Applications with Unity, ARCore, ARKit, and Vuforia, Packt Publishing Ltd."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Xu, J., Xue, F., Chiaradia, A., Lu, W., and Cao, J. (2020). Indoor-Outdoor Navigation without Beacons: Compensating Smartphone AR Positioning Errors with 3D Pedestrian Network. Construction Research Congress 2020: Infrastructure Systems and Sustainability, American Society of Civil Engineers.","DOI":"10.1061\/9780784482858.049"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.autcon.2015.12.008","article-title":"Automatic reconstruction of 3D building models from scanned 2D floor plans","volume":"63","author":"Gimenez","year":"2016","journal-title":"Autom. Constr."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Han, J., Yin, P., He, Y., and Gu, F. (2016). Enhanced ICP for the registration of large-scale 3D environment models: An experimental study. Sensors, 16.","DOI":"10.3390\/s16020228"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lin, W.Y., Liu, S., Jiang, N., Do, M.N., Tan, P., and Lu, J. (2016, January 8\u201316). RepMatch: Robust feature matching and pose for reconstructing modern cities. Proceedings of the European Conference on Computer Vision, Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46448-0_34"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1162\/106365603321828970","article-title":"Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES)","volume":"11","author":"Hansen","year":"2003","journal-title":"Evol. Comput."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1007\/BF00941892","article-title":"Lipschitzian optimization without the Lipschitz constant","volume":"79","author":"Jones","year":"1993","journal-title":"J. Optim. Theory Appl."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1093\/comjnl\/7.4.308","article-title":"A simplex method for function minimization","volume":"7","author":"Nelder","year":"1965","journal-title":"Comput. J."},{"key":"ref_25","unstructured":"Johnson, A.E., and Hebert, M. (1998, January 25). Efficient multiple model recognition in cluttered 3-D scenes. Proceedings of the 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No. 98CB36231), Santa Barbara, CA, USA."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1023\/A:1007981719186","article-title":"Point signatures: A new representation for 3d object recognition","volume":"25","author":"Chua","year":"1997","journal-title":"Int. J. Comput. Vis."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Rusu, R.B., Blodow, N., and Beetz, M. (2009, January 12\u201317). Fast point feature histograms (FPFH) for 3D registration. Proceedings of the 2009 IEEE International Conference on Robotics and Automation, Kobe, Japan.","DOI":"10.1109\/ROBOT.2009.5152473"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Zeng, A., Song, S., Nie\u00dfner, M., Fisher, M., Xiao, J., and Funkhouser, T. (2017, January 21\u201326). 3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.29"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Choy, C., Park, J., and Koltun, V. (November, January 27). Fully Convolutional Geometric Features. Proceedings of the 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), Seoul, Korea.","DOI":"10.1109\/ICCV.2019.00905"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Yew, Z.J., and Lee, G.H. (2018, January 8\u201314). 3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration. Proceedings of the European Conference on Computer Vision, Munich, Germany.","DOI":"10.1007\/978-3-030-01267-0_37"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Deng, H., Birdal, T., and Ilic, S. (2018, January 18\u201322). PPFNet: Global Context Aware Local Features for Robust 3D Point Matching. Proceedings of the 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00028"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1109\/34.121791","article-title":"A method for registration of 3-D shapes","volume":"14","author":"Besl","year":"1992","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/0262-8856(92)90066-C","article-title":"Object modelling by registration of multiple range images","volume":"10","author":"Chen","year":"1992","journal-title":"Image Vis. Comput."},{"key":"ref_34","unstructured":"Rusinkiewicz, S., and Levoy, M. (June, January 28). Efficient variants of the ICP algorithm. Proceedings of the Third International Conference on 3-D Digital Imaging and Modeling, Quebec City, QC, Canada."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2262","DOI":"10.1109\/TPAMI.2010.46","article-title":"Point set registration: Coherent point drift","volume":"32","author":"Myronenko","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2241","DOI":"10.1109\/TPAMI.2015.2513405","article-title":"Go-ICP: A globally optimal solution to 3D ICP point-set registration","volume":"38","author":"Yang","year":"2015","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Eckart, B., Kim, K., and Kautz, J. (2018, January 8\u201314). Hgmr: Hierarchical gaussian mixtures for adaptive 3d registration. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01267-0_43"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1109\/TRO.2020.3033695","article-title":"TEASER: Fast and certifiable point cloud registration","volume":"37","author":"Yang","year":"2020","journal-title":"IEEE Trans. Robot."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Wang, Y., and Solomon, J. (November, January 27). Deep Closest Point: Learning Representations for Point Cloud Registration. Proceedings of the 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), Seoul, Korea.","DOI":"10.1109\/ICCV.2019.00362"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Choy, C., Dong, W., and Koltun, V. (2020, January 14\u201319). Deep Global Registration. Proceedings of the 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA.","DOI":"10.1109\/CVPR42600.2020.00259"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.isprsjprs.2019.02.015","article-title":"Pairwise coarse registration of point clouds in urban scenes using voxel-based 4-planes congruent sets","volume":"151","author":"Xu","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2530","DOI":"10.1109\/TGRS.2019.2952086","article-title":"PLADE: A Plane-Based Descriptor for Point Cloud Registration With Small Overlap","volume":"58","author":"Chen","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.isprsjprs.2018.04.004","article-title":"Three-dimensional building fa\u00e7ade segmentation and opening area detection from point clouds","volume":"143","author":"Zolanvari","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2019.04.004","article-title":"Scale invariant line-based co-registration of multimodal aerial data using L1 minimization of spatial and angular deviations","volume":"152","author":"Polewski","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.autcon.2018.05.009","article-title":"Automatic building information model reconstruction in high-density urban areas: Augmenting multi-source data with architectural knowledge","volume":"93","author":"Chen","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"13945","DOI":"10.3390\/rs71013945","article-title":"Semantic decomposition and reconstruction of compound buildings with symmetric roofs from LiDAR data and aerial imagery","volume":"7","author":"Wang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2517348","article-title":"Coupled structure-from-motion and 3D symmetry detection for urban facades","volume":"33","author":"Ceylan","year":"2014","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1109\/JSTARS.2017.2752765","article-title":"A symmetry-based method for LiDAR point registration","volume":"11","author":"Cheng","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.isprsjprs.2018.12.005","article-title":"A derivative-free optimization-based approach for detecting architectural symmetries from 3D point clouds","volume":"148","author":"Xue","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"100965","DOI":"10.1016\/j.aei.2019.100965","article-title":"BIM reconstruction from 3D point clouds: A semantic registration approach based on multimodal optimization and architectural design knowledge","volume":"42","author":"Xue","year":"2019","journal-title":"Adv. Eng. Inform."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"103338","DOI":"10.1016\/j.autcon.2020.103338","article-title":"Unsupervised reconstruction of Building Information Modeling wall objects from point cloud data","volume":"120","author":"Bassier","year":"2020","journal-title":"Autom. Constr."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.isprsjprs.2018.03.025","article-title":"Semantic line framework-based indoor building modeling using backpacked laser scanning point cloud","volume":"143","author":"Wang","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"103109","DOI":"10.1016\/j.autcon.2020.103109","article-title":"Indoor 3D reconstruction from point clouds for optimal routing in complex buildings to support disaster management","volume":"113","author":"Nikoohemat","year":"2020","journal-title":"Autom. Constr."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.isprsjprs.2019.03.017","article-title":"Automatic reconstruction of fully volumetric 3D building models from oriented point clouds","volume":"151","author":"Ochmann","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1016\/j.aei.2018.10.007","article-title":"Automated 3D volumetric reconstruction of multiple-room building interiors for as-built BIM","volume":"38","author":"Jung","year":"2018","journal-title":"Adv. Eng. Inform."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Murali, S., Speciale, P., Oswald, M.R., and Pollefeys, M. (2017, January 24\u201328). Indoor Scan2BIM: Building information models of house interiors. Proceedings of the 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada.","DOI":"10.1109\/IROS.2017.8206513"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Liu, C., Wu, J., Kohli, P., and Furukawa, Y. (2017, January 22\u201329). Raster-to-Vector: Revisiting Floorplan Transformation. Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy.","DOI":"10.1109\/ICCV.2017.241"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Wu, Y., Shang, J., Chen, P., Zlatanova, S., Hu, X., and Zhou, Z. (2020). Indoor mapping and modeling by parsing floor plan images. Int. J. Geogr. Inf. Sci.","DOI":"10.1080\/13658816.2020.1781130"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Wijmans, E., and Furukawa, Y. (2017, January 21\u201326). Exploiting 2D Floorplan for Building-Scale Panorama RGBD Alignment. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.156"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1109\/34.295913","article-title":"Seeded region growing","volume":"16","author":"Adams","year":"1994","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Turner, E., and Zakhor, A. (2012, January 13\u201315). Watertight as-built architectural floor plans generated from laser range data. Proceedings of the 2012 Second International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission, Zurich, Switzerland.","DOI":"10.1109\/3DIMPVT.2012.80"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1109\/34.574800","article-title":"3D symmetry detection using the extended Gaussian image","volume":"19","author":"Sun","year":"1997","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1221","DOI":"10.1109\/TPAMI.2007.1032","article-title":"An approximate and efficient method for optimal rotation alignment of 3D models","volume":"29","author":"Kazhdan","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_64","unstructured":"Rowan, T.H. (1990). Functional Stability Analysis of Numerical Algorithms. [Ph.D. Thesis, The University of Texas at Austin]."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1080\/10867651.2004.10487596","article-title":"An image inpainting technique based on the fast marching method","volume":"9","author":"Telea","year":"2004","journal-title":"J. Graph. Tools"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"12813","DOI":"10.1038\/s41598-019-49256-0","article-title":"SPOT3D: Spatial positioning toolbox for head markers using 3D scans","volume":"9","author":"Taberna","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_67","unstructured":"Benazera, E. (2020, November 02). Libcmaes: A Multithreaded C++11 Library with Python Bindings for High Performance Blackbox Stochastic Optimization Using the CMA-ES Algorithm for Covariance Matrix Adaptation Evolution Strategy. Available online: https:\/\/github.com\/beniz\/libcmaes."},{"key":"ref_68","unstructured":"Steven, J. (2020, November 02). NLopt: A Free\/Open-Source Library for Nonlinear Optimization. Available online: https:\/\/nlopt.readthedocs.io\/en\/latest\/."},{"key":"ref_69","unstructured":"Tanaka, K., Schmitz, P., Ciganovic, M., and Kumar, P. (2020, November 02). Probreg: Probablistic Point Cloud Registration Library. Available online: https:\/\/probreg.readthedocs.io\/en\/latest\/."},{"key":"ref_70","unstructured":"Srinivasan, R. (2020, November 02). Go-icp_cython: A Cython Version of the Original Go-ICP. Available online: https:\/\/github.com\/aalavandhaann\/go-icp_cython."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"1199","DOI":"10.1109\/TVCG.2012.310","article-title":"Registration of 3D point clouds and meshes: A survey from rigid to nonrigid","volume":"19","author":"Tam","year":"2012","journal-title":"IEEE Trans. Vis. Comput. Graph."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/10\/1882\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:59:23Z","timestamp":1760162363000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/10\/1882"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,11]]},"references-count":71,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13101882"],"URL":"https:\/\/doi.org\/10.3390\/rs13101882","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,11]]}}}