{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T12:50:52Z","timestamp":1761396652158,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,10,29]],"date-time":"2023-10-29T00:00:00Z","timestamp":1698537600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation (NSF)","doi-asserted-by":"publisher","award":["2020534"],"award-info":[{"award-number":["2020534"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Institute of Computational Sciences at University of Tenneessee, Knoxville","award":["2020534"],"award-info":[{"award-number":["2020534"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The integration of structure from motion (SFM) and unmanned aerial vehicle (UAV) technologies has allowed for the generation of very high-resolution three-dimensional (3D) point cloud data (up to millimeters) to detect and monitor surface changes. However, a bottleneck still exists in accurately and rapidly registering the point clouds at different times. The existing point cloud registration algorithms, such as the Iterative Closest Point (ICP) and the Fast Global Registration (FGR) method, were mainly developed for the registration of small and static point cloud data, and do not perform well when dealing with large point cloud data with potential changes over time. In particular, registering large data is computationally expensive, and the inclusion of changing objects reduces the accuracy of the registration. In this paper, we develop an AI-based workflow to ensure high-quality registration of the point clouds generated using UAV-collected photos. We first detect stable objects from the ortho-photo produced by the same set of UAV-collected photos to segment the point clouds of these objects. Registration is then performed only on the partial data with these stable objects. The application of this workflow using the UAV data collected from three erosion plots at the East Tennessee Research and Education Center indicates that our workflow outperforms the existing algorithms in both computational speed and accuracy. This AI-based workflow significantly improves computational efficiency and avoids the impact of changing objects for the registration of large point cloud data.<\/jats:p>","DOI":"10.3390\/rs15215163","type":"journal-article","created":{"date-parts":[[2023,10,29]],"date-time":"2023-10-29T05:01:08Z","timestamp":1698555668000},"page":"5163","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An AI-Based Workflow for Fast Registration of UAV-Produced 3D Point Clouds"],"prefix":"10.3390","volume":"15","author":[{"given":"Yong","family":"Feng","sequence":"first","affiliation":[{"name":"Department of Computer Science, The City University of Hong Kong, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ka Lun","family":"Leung","sequence":"additional","affiliation":[{"name":"Department of Mathematics, The Chinese University of Hong Kong, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3722-8960","authenticated-orcid":false,"given":"Yingkui","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Geography and Sustainability, University of Tennessee, Knoxville, TN 37996, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kwai Lam","family":"Wong","sequence":"additional","affiliation":[{"name":"Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1111\/phor.12115","article-title":"Analysis of different methods for 3D reconstruction of natural surfaces from parallel-axes UAV images","volume":"30","author":"Eltner","year":"2015","journal-title":"Photogramm. Rec."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"114477","DOI":"10.1016\/j.geoderma.2020.114477","article-title":"High-Resolution Monitoring of Diffuse (Sheet or Interrill) Erosion Using Structure-from-Motion","volume":"375","author":"Quinton","year":"2020","journal-title":"Geoderma"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3390","DOI":"10.3390\/rs4113390","article-title":"Unmanned aerial vehicle (UAV) for monitoring soil erosion in Morocco","volume":"4","author":"Marzolff","year":"2012","journal-title":"Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Pavlis, T.L., and Serpa, L.F. (2023). Accuracy of Structure-from-Motion\/Multiview Stereo Terrain Models: A Practical Assessment for Applications in Field Geology. Geosciences, 13.","DOI":"10.3390\/geosciences13070217"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4026","DOI":"10.3390\/rs70404026","article-title":"Evaluating multispectral images and vegetation indices for precision farming applications from UAV images","volume":"7","author":"Candiago","year":"2015","journal-title":"Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"224","DOI":"10.26833\/ijeg.1115608","article-title":"Identification of potential zones on the estimation of direct runoff and soil erosion for an ungauged watershed based on remote sensing and GIS techniques","volume":"8","author":"Patil","year":"2023","journal-title":"Int. J. Eng. Geosci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.cag.2015.07.004","article-title":"Reconstructing building mass models from UAV images","volume":"54","author":"Li","year":"2016","journal-title":"Comput. Graph."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Yakar, M., and Dogan, Y. (2019, January 12\u201315). 3D Reconstruction of Residential Areas with SfM Photogrammetry. Proceedings of the 1st Springer Conference of the Arabian Journal of Geosciences (CAJG-1), Sousse, Tunisia.","DOI":"10.1007\/978-3-030-01440-7_18"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1002\/esp.3366","article-title":"Topographic structure from motion: A new development in photogrammetric measurement","volume":"38","author":"Fonstad","year":"2012","journal-title":"Earth Surf. Process Landforms"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1177\/0309133315615805","article-title":"Structure from motion photogrammetry in physical geography","volume":"40","author":"Smith","year":"2015","journal-title":"Prog. Phys. Geogr. Earth Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"359","DOI":"10.5194\/esurf-4-359-2016","article-title":"Image-based surface reconstruction in geomorphometry \u2013 merits, limits and developments","volume":"4","author":"Eltner","year":"2016","journal-title":"Earth Surf. Dyn."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.geomorph.2014.01.006","article-title":"Modeling the topography of shallow braided rivers using Structure-from-Motion photogrammetry","volume":"213","author":"Javernick","year":"2014","journal-title":"Geomorphology"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1016\/j.measurement.2019.07.015","article-title":"The use of TLS and UAV methods for measurement of the repose angle of granular materials in terrain conditions","volume":"146","author":"Klapa","year":"2019","journal-title":"Measurement"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.geomorph.2014.02.016","article-title":"The evaluation of unmanned aerial system-based photogrammetry and terrestrial laser scanning to generate DEMs of agricultural watersheds","volume":"214","author":"Debouche","year":"2014","journal-title":"Geomorphology"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"301","DOI":"10.26833\/ijeg.1178260","article-title":"Methodology of real-time 3D point cloud mapping with UAV lidar","volume":"8","author":"Candan","year":"2023","journal-title":"Int. J. Eng. Geosci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"32","DOI":"10.53093\/mephoj.1290231","article-title":"Deterioration analysis of historical village house structure in Mersin Kanl\u0131divane archaeological area by UAV method","volume":"5","author":"Karatas","year":"2023","journal-title":"Mersin Photogramm. J."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"00012","DOI":"10.1051\/e3sconf\/20182600012","article-title":"The analysis of the accuracy of spatial models using photogrammetric software: Agisoft Photoscan and Pix4D","volume":"Volume 26","author":"Barbasiewicz","year":"2018","journal-title":"E3S Web of Conferences"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5016","DOI":"10.1080\/01431161.2017.1420942","article-title":"Investigating the performances of commercial and non-commercial software for ground filtering of UAV-based point clouds","volume":"39","author":"Yilmaz","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"55","DOI":"10.5194\/isprs-annals-IV-4-W4-55-2017","article-title":"Comparison of UAS-based photogrammetry software for 3D point cloud generation: A survey over a historical site","volume":"IV-4\/W4","author":"Alidoost","year":"2017","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_20","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_21","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":"2016","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhou, Q., Park, J., and Koltun, V. (2016, January 11\u201314). Fast global registration. Proceedings of the 14th European Conference (ECCV 2016), Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46475-6_47"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Jost, T., and H\u00fcgli, H. (2002, January 16\u201318). Fast ICP algorithms for shape registration. Proceedings of the 24th DAGM Symposium, Zurich, Switzerland.","DOI":"10.1007\/3-540-45783-6_12"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/j.imavis.2003.09.004","article-title":"Robust registration of 2D and 3D point sets","volume":"21","author":"Fitzgibbon","year":"2002","journal-title":"Image Vis. Comput."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Granger, S., and Pennec, X. (2002, January 28\u201331). Multi-scale EM-ICP: A fast and robust approach for surface registration. Proceedings of the 7th European Conference on Computer Vision (ECCV 2002), Copenhagen, Denmark.","DOI":"10.1007\/3-540-47979-1_28"},{"key":"ref_26","first-page":"1911","article-title":"Object detection: Yolo vs Faster R-CNN","volume":"4","author":"Joiya","year":"2022","journal-title":"Int. Res. J. Mod. Eng. Technol. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1023\/B:AIRE.0000045502.10941.a9","article-title":"A survey of outlier detection methodologies","volume":"22","author":"Hodge","year":"2004","journal-title":"Artif. Intell. Rev."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Bailey, G., Li, Y., McKinney, N., Yoder, D., Wright, W., and Washington-Allen, R. (2022). Las2DoD: Change Detection Based on Digital Elevation Models Derived from Dense Point Clouds with Spatially Varied Uncertainty. Remote Sens., 14.","DOI":"10.3390\/rs14071537"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Bailey, G., Li, Y., McKinney, N., Yoder, D., Wright, W., and Herrero, H. (2022). Comparison of Ground Point Filtering Algorithms for High-Density Point Clouds Collected by Terrestrial LiDAR. Remote Sens., 14.","DOI":"10.3390\/rs14194776"},{"key":"ref_30","first-page":"1765","article-title":"Fast and robust normal estimation for point clouds with sharp features","volume":"31","author":"Boulch","year":"2012","journal-title":"Eurographics Symp. Geom. Process."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/21\/5163\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:13:39Z","timestamp":1760130819000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/21\/5163"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,29]]},"references-count":30,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2023,11]]}},"alternative-id":["rs15215163"],"URL":"https:\/\/doi.org\/10.3390\/rs15215163","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,10,29]]}}}