{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T00:49:03Z","timestamp":1782175743077,"version":"3.54.5"},"reference-count":48,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T00:00:00Z","timestamp":1684368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Anhui Province Natural Science Foundation","award":["2208085QD106"],"award-info":[{"award-number":["2208085QD106"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Image-based refined 3D reconstruction relies on high-resolution and multi-angle images of scenes. The assistance of multi-rotor drones and gimbal provides great convenience for image acquisition. However, capturing images with manual control generally takes a long time. It could easily lead to redundant or insufficient local area coverage, resulting in poor quality of the reconstructed model. We propose a surface geometric primitive-guided UAV path planning method (SGP-G) that aims to automatically and quickly plan a collision-free path to capture fewer images, based on which high-quality models can be obtained. The geometric primitives are extracted by plane segmentation on the proxy, which performs three main functions. First, a more representative evaluation of the reconstructability of the whole scene is realized. Second, two optimization strategies for different geometric primitives are executed to quickly generate a near-global optimized set of viewpoints. Third, regularly arranged viewpoints are generated to improve the efficiency of image acquisition. Experiments on virtual and real scenes demonstrate the remarkable performance of our method. Compared with the state of the art, we accomplish the planning of the photographic path with higher efficiency in a relatively simple way, achieving equivalent and even higher quality of the reconstructed model with fewer images.<\/jats:p>","DOI":"10.3390\/rs15102632","type":"journal-article","created":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T06:32:58Z","timestamp":1684391578000},"page":"2632","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Geometric Primitive-Guided UAV Path Planning for High-Quality Image-Based Reconstruction"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1670-6748","authenticated-orcid":false,"given":"Hao","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1419-5326","authenticated-orcid":false,"given":"Zheng","family":"Ji","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangyu","family":"You","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuchen","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingfeng","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Zhao","sequence":"additional","affiliation":[{"name":"Wuhan Xianheng Information Technology Ltd., Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shan","family":"Lin","sequence":"additional","affiliation":[{"name":"Wuhan Xianheng Information Technology Ltd., Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangxiang","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer and Information, Anhui Polytechnic University, Wuhu 241000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ben Ahmed, M., Boudhir, A.A., Santos, D., El Aroussi, M., and Karas, \u0130.R. (2020). Innovations in Smart Cities Applications, Springer International Publishing. [3rd ed.].","DOI":"10.1007\/978-3-030-37629-1"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.aei.2018.05.005","article-title":"A Review of 3D Reconstruction Techniques in Civil Engineering and Their Applications","volume":"37","author":"Ma","year":"2018","journal-title":"Adv. Eng. Inform."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.jas.2013.08.020","article-title":"On Introducing an Image-Based 3D Reconstruction Method in Archaeological Excavation Practice","volume":"41","author":"Herremans","year":"2014","journal-title":"J. Archaeol. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/0600000052","article-title":"Multi-View Stereo: A Tutorial","volume":"9","author":"Furukawa","year":"2015","journal-title":"Found. Trends\u00ae Comput. Graph. Vis."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.geomorph.2012.08.021","article-title":"\u2018Structure-from-Motion\u2019 Photogrammetry: A Low-Cost, Effective Tool for Geoscience Applications","volume":"179","author":"Westoby","year":"2012","journal-title":"Geomorphology"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Leibe, B., Matas, J., Sebe, N., and Welling, M. (2016). Proceedings of the Computer Vision\u2014ECCV 2016, Amsterdam, The Netherlands, 11\u201314 October 2016, Springer International Publishing.","DOI":"10.1007\/978-3-319-46478-7"},{"key":"ref_7","unstructured":"Seitz, S.M., Curless, B., Diebel, J., Scharstein, D., and Szeliski, R. (2006, January 17\u201322). A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms. Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR\u201906), New York, NY, USA."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1145\/1141911.1141964","article-title":"Photo Tourism: Exploring Photo Collections in 3D","volume":"25","author":"Snavely","year":"2006","journal-title":"ACM Trans. Graph."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Ferrari, V., Hebert, M., Sminchisescu, C., and Weiss, Y. (2018, January 8\u201314). MVSNet: Depth Inference for Unstructured Multi-View Stereo. Proceedings of the Computer Vision\u2014ECCV 2018, Munich, Germany.","DOI":"10.1007\/978-3-030-01249-6"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Yao, Y., Luo, Z., Li, S., Shen, T., Fang, T., and Quan, L. (2019, January 16\u201317). Recurrent MVSNet for High-Resolution Multi-View Stereo Depth Inference. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.00567"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Goesele, M., Snavely, N., Curless, B., Hoppe, H., and Seitz, S.M. (2007, January 14\u201321). Multi-View Stereo for Community Photo Collections. Proceedings of the 2007 IEEE 11th International Conference on Computer Vision, Rio De Janeiro, Brazil.","DOI":"10.1109\/ICCV.2007.4408933"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Hornung, A., Zeng, B., and Kobbelt, L. (2008, January 23\u201328). Image Selection for Improved Multi-View Stereo. Proceedings of the 2008 IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska.","DOI":"10.1109\/CVPR.2008.4587688"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.aei.2015.01.012","article-title":"Automated As-Built 3D Reconstruction of Civil Infrastructure Using Computer Vision: Achievements, Opportunities, and Challenges","volume":"29","author":"Fathi","year":"2015","journal-title":"Adv. Eng. Inform."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"33","DOI":"10.5194\/isprs-annals-V-1-2022-33-2022","article-title":"An object-oriented uav 3d path planning method applied in cultural heritage documentation","volume":"V-1\u20132022","author":"Liu","year":"2022","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3233794","article-title":"Plan3D: Viewpoint and Trajectory Optimization for Aerial Multi-View Stereo Reconstruction","volume":"38","author":"Hepp","year":"2019","journal-title":"ACM Trans. Graph."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Roberts, M., Shah, S., Dey, D., Truong, A., Sinha, S., Kapoor, A., Hanrahan, P., and Joshi, N. (2017, January 22\u201329). Submodular Trajectory Optimization for Aerial 3D Scanning. Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy.","DOI":"10.1109\/ICCV.2017.569"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Koch, T., K\u00f6rner, M., and Fraundorfer, F. (2019). Automatic and Semantically-Aware 3D UAV Flight Planning for Image-Based 3D Reconstruction. Remote Sens., 11.","DOI":"10.3390\/rs11131550"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Li, T., Hailes, S., Julier, S., and Liu, M. (2017, January 5\u20138). UAV-Based SLAM and 3D Reconstruction System. Proceedings of the 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO), Macau, China.","DOI":"10.1109\/ROBIO.2017.8324795"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12518-013-0120-x","article-title":"UAV for 3D Mapping Applications: A Review","volume":"6","author":"Nex","year":"2014","journal-title":"Appl. Geomat."},{"key":"ref_20","first-page":"1","article-title":"Aerial Path Planning for Urban Scene Reconstruction: A Continuous Optimization Method and Benchmark","volume":"37","author":"Smith","year":"2018","journal-title":"ACM Trans. Graph."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Maboudi, M., Homaei, M., Song, S., Malihi, S., Saadatseresht, M., and Gerke, M. (2022). A Review on Viewpoints and Path-Planning for UAV-Based 3D Reconstruction. arXiv.","DOI":"10.1109\/JSTARS.2023.3276427"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Ferrari, V., Hebert, M., Sminchisescu, C., and Weiss, Y. (2018, January 8\u201314). Learn-to-Score: Efficient 3D Scene Exploration by Predicting View Utility. Proceedings of the Computer Vision\u2014ECCV 2018, Munich, Germany.","DOI":"10.1007\/978-3-030-01249-6"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Kuang, Q., Wu, J., Pan, J., and Zhou, B. (August, January 31). Real-Time UAV Path Planning for Autonomous Urban Scene Reconstruction. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France.","DOI":"10.1109\/ICRA40945.2020.9196558"},{"key":"ref_24","first-page":"1","article-title":"Aerial Path Planning for Online Real-Time Exploration and Offline High-Quality Reconstruction of Large-Scale Urban Scenes","volume":"40","author":"Liu","year":"2021","journal-title":"ACM Trans. Graph."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Palazzolo, E., and Stachniss, C. (2018). Effective Exploration for MAVs Based on the Expected Information Gain. Drones, 2.","DOI":"10.3390\/drones2010009"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"203:1","DOI":"10.1145\/2661229.2661242","article-title":"Quality-Driven Poisson-Guided Autoscanning","volume":"33","author":"Wu","year":"2014","journal-title":"ACM Trans. Graph."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"238:1","DOI":"10.1145\/2980179.2980224","article-title":"3D Attention-Driven Depth Acquisition for Object Identification","volume":"35","author":"Xu","year":"2016","journal-title":"ACM Trans. Graph."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1431","DOI":"10.1007\/s10514-020-09936-7","article-title":"Online Coverage and Inspection Planning for 3D Modeling","volume":"44","author":"Song","year":"2020","journal-title":"Auton. Robot."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1500","DOI":"10.1109\/LRA.2020.2969191","article-title":"An Efficient Sampling-Based Method for Online Informative Path Planning in Unknown Environments","volume":"5","author":"Schmid","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3478513.3480500","article-title":"Continuous Aerial Path Planning for 3D Urban Scene Reconstruction","volume":"40","author":"Zhang","year":"2021","journal-title":"ACM Trans. Graph."},{"key":"ref_31","first-page":"1","article-title":"Offsite Aerial Path Planning for Efficient Urban Scene Reconstruction","volume":"39","author":"Zhou","year":"2020","journal-title":"ACM Trans. Graph."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Yan, F., Xia, E., Li, Z., and Zhou, Z. (2021). Sampling-Based Path Planning for High-Quality Aerial 3D Reconstruction of Urban Scenes. Remote Sens., 13.","DOI":"10.3390\/rs13050989"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1016\/j.isprsjprs.2018.11.004","article-title":"A Multi-UAV Cooperative Route Planning Methodology for 3D Fine-Resolution Building Model Reconstruction","volume":"146","author":"Zheng","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_34","first-page":"1","article-title":"Learning Reconstructability for Drone Aerial Path Planning","volume":"41","author":"Liu","year":"2022","journal-title":"ACM Trans. Graph."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1109\/JSTARS.2022.3233359","article-title":"Optimized Views Photogrammetry: Precision Analysis and a Large-Scale Case Study in Qingdao","volume":"16","author":"Li","year":"2023","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_36","unstructured":"Hoppe, C., Wendel, A., Zollmann, S., Pirker, K., Irschara, A., Bischof, H., and Kluckner, S. (2012, January 3\u20137). Photogrammetric Camera Network Design for Micro Aerial Vehicles. Proceedings of the Computer Vision Winter Workshop, Waikoloa, HI, USA."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1016\/j.isprsjprs.2020.07.010","article-title":"Structure-Aware Building Mesh Polygonization","volume":"167","author":"Bouzas","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"4634","DOI":"10.1109\/LRA.2020.3002212","article-title":"Polylidar\u2014Polygons From Triangular Meshes","volume":"5","author":"Castagno","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Castagno, J., and Atkins, E. (2020). Polylidar3D-Fast Polygon Extraction from 3D Data. Sensors, 20.","DOI":"10.3390\/s20174819"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"112","DOI":"10.3138\/FM57-6770-U75U-7727","article-title":"Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or Its Caricature","volume":"10","author":"Douglas","year":"1973","journal-title":"Cartographica"},{"key":"ref_41","unstructured":"Hershberger, J., and Snoeyink, J. (1992, January 3\u20137). Speeding Up the Douglas-Peucker Line-Simplification Algorithm. Proceedings of the 5th International Symposium on Spatial Data Handling, Charleston, SC, USA."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Peng, C., and Isler, V. (2019, January 20\u201324). Adaptive View Planning for Aerial 3D Reconstruction. Proceedings of the 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada.","DOI":"10.1109\/ICRA.2019.8793532"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"58383","DOI":"10.1109\/ACCESS.2018.2875040","article-title":"Comprehensive Energy Consumption Model for Unmanned Aerial Vehicles, Based on Empirical Studies of Battery Performance","volume":"6","author":"Abeywickrama","year":"2018","journal-title":"IEEE Access"},{"key":"ref_44","unstructured":"Thibbotuwawa, A., Nielsen, P., Zbigniew, B., and Bocewicz, G. (2019). Information Systems Architecture and Technology, Proceedings of the 39th International Conference on Information Systems Architecture and Technology\u2014ISAT 2018, Nysa, Polska, 16\u201318 September 2018, Springer."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1109\/4235.585892","article-title":"Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem","volume":"1","author":"Dorigo","year":"1997","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.jpdc.2016.04.014","article-title":"The GPU-Based Parallel Ant Colony System","volume":"98","author":"Skinderowicz","year":"2016","journal-title":"J. Parallel Distrib. Comput."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., and Hassner, T. (2022, January 23\u201327). Capturing, Reconstructing, and Simulating: The UrbanScene3D Dataset. Proceedings of the Computer Vision\u2014ECCV 2022, Tel Aviv, Israel.","DOI":"10.1007\/978-3-031-20056-4"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"972","DOI":"10.1109\/32.92917","article-title":"A Linear Algorithm for Generating Random Numbers with a given Distribution","volume":"17","author":"Vose","year":"1991","journal-title":"IEEE Trans. Softw. Eng."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/10\/2632\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:37:43Z","timestamp":1760125063000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/10\/2632"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,18]]},"references-count":48,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2023,5]]}},"alternative-id":["rs15102632"],"URL":"https:\/\/doi.org\/10.3390\/rs15102632","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,18]]}}}