Akram Akbar , Chun Liu , Hangbin Wu , Shoujun Jia , Zeran Xu
{"title":"场景信息指导下的航空摄影测量任务重构,实现详细级别的建筑物重建","authors":"Akram Akbar , Chun Liu , Hangbin Wu , Shoujun Jia , Zeran Xu","doi":"10.1016/j.aei.2024.102913","DOIUrl":null,"url":null,"abstract":"<div><div>Real 3D building models have become indispensable data sources for building spatial information bases for smart cities by leveraging structural correlations and rich semantic expressions of real-world scene entities. The essential prerequisite for real 3D reconstruction is real-time and dynamic detailed-level observations. Low-altitude multicopter UAV platforms are optimal for automatic and periodic building scene observations. However, there are still several challenges in UAV-based path planning for real 3D data capture while maintaining the overall fidelity of architectural details due to observational scale variations, surrounding uncertainties, structural complexity, and topological delicacy. We propose a scene information guided aerial photogrammetric mission recomposition method in response to this challenge. Depending on the architectural complexity, the two proposed observation patterns, parallel inspection and surface enveloping, can be recomposed to achieve UAV obstacle avoidance and complete coverage of individual buildings in a restricted space, capturing global surface detail with millimeter resolution and low texture distortion. The virtual simulation environment, which is constructed based on the semantics and elevation values of the surroundings, provides a basis for selecting the observation pattern and optimal flight parameters based on the reconstruction requirements of the building. In order to achieve quality control of 3D reconstruction models, this paper introduces a reconstruction quality assessment scheme consisting of four quantitative evaluation metrics, namely coverage, resolution distribution, texture distortion score, and geometric accuracy, which effectively establishes a close relationship between mission planning and 3D reconstruction. The observation capability of the proposed method is better than other typical observation patterns, obtaining a model of globally homogeneous resolution distribution over the main body of the building, reaching an average level of 7.01 mm and the highest level of 2.12 mm (façade region), which can provide high-quality data for the semantic extraction and instantiation of multiple surface elements of buildings.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"62 ","pages":"Article 102913"},"PeriodicalIF":8.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scene information guided aerial photogrammetric mission recomposition towards detailed level building reconstruction\",\"authors\":\"Akram Akbar , Chun Liu , Hangbin Wu , Shoujun Jia , Zeran Xu\",\"doi\":\"10.1016/j.aei.2024.102913\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Real 3D building models have become indispensable data sources for building spatial information bases for smart cities by leveraging structural correlations and rich semantic expressions of real-world scene entities. The essential prerequisite for real 3D reconstruction is real-time and dynamic detailed-level observations. Low-altitude multicopter UAV platforms are optimal for automatic and periodic building scene observations. However, there are still several challenges in UAV-based path planning for real 3D data capture while maintaining the overall fidelity of architectural details due to observational scale variations, surrounding uncertainties, structural complexity, and topological delicacy. We propose a scene information guided aerial photogrammetric mission recomposition method in response to this challenge. Depending on the architectural complexity, the two proposed observation patterns, parallel inspection and surface enveloping, can be recomposed to achieve UAV obstacle avoidance and complete coverage of individual buildings in a restricted space, capturing global surface detail with millimeter resolution and low texture distortion. The virtual simulation environment, which is constructed based on the semantics and elevation values of the surroundings, provides a basis for selecting the observation pattern and optimal flight parameters based on the reconstruction requirements of the building. In order to achieve quality control of 3D reconstruction models, this paper introduces a reconstruction quality assessment scheme consisting of four quantitative evaluation metrics, namely coverage, resolution distribution, texture distortion score, and geometric accuracy, which effectively establishes a close relationship between mission planning and 3D reconstruction. The observation capability of the proposed method is better than other typical observation patterns, obtaining a model of globally homogeneous resolution distribution over the main body of the building, reaching an average level of 7.01 mm and the highest level of 2.12 mm (façade region), which can provide high-quality data for the semantic extraction and instantiation of multiple surface elements of buildings.</div></div>\",\"PeriodicalId\":50941,\"journal\":{\"name\":\"Advanced Engineering Informatics\",\"volume\":\"62 \",\"pages\":\"Article 102913\"},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Engineering Informatics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1474034624005640\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Engineering Informatics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1474034624005640","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Scene information guided aerial photogrammetric mission recomposition towards detailed level building reconstruction
Real 3D building models have become indispensable data sources for building spatial information bases for smart cities by leveraging structural correlations and rich semantic expressions of real-world scene entities. The essential prerequisite for real 3D reconstruction is real-time and dynamic detailed-level observations. Low-altitude multicopter UAV platforms are optimal for automatic and periodic building scene observations. However, there are still several challenges in UAV-based path planning for real 3D data capture while maintaining the overall fidelity of architectural details due to observational scale variations, surrounding uncertainties, structural complexity, and topological delicacy. We propose a scene information guided aerial photogrammetric mission recomposition method in response to this challenge. Depending on the architectural complexity, the two proposed observation patterns, parallel inspection and surface enveloping, can be recomposed to achieve UAV obstacle avoidance and complete coverage of individual buildings in a restricted space, capturing global surface detail with millimeter resolution and low texture distortion. The virtual simulation environment, which is constructed based on the semantics and elevation values of the surroundings, provides a basis for selecting the observation pattern and optimal flight parameters based on the reconstruction requirements of the building. In order to achieve quality control of 3D reconstruction models, this paper introduces a reconstruction quality assessment scheme consisting of four quantitative evaluation metrics, namely coverage, resolution distribution, texture distortion score, and geometric accuracy, which effectively establishes a close relationship between mission planning and 3D reconstruction. The observation capability of the proposed method is better than other typical observation patterns, obtaining a model of globally homogeneous resolution distribution over the main body of the building, reaching an average level of 7.01 mm and the highest level of 2.12 mm (façade region), which can provide high-quality data for the semantic extraction and instantiation of multiple surface elements of buildings.
期刊介绍:
Advanced Engineering Informatics is an international Journal that solicits research papers with an emphasis on 'knowledge' and 'engineering applications'. The Journal seeks original papers that report progress in applying methods of engineering informatics. These papers should have engineering relevance and help provide a scientific base for more reliable, spontaneous, and creative engineering decision-making. Additionally, papers should demonstrate the science of supporting knowledge-intensive engineering tasks and validate the generality, power, and scalability of new methods through rigorous evaluation, preferably both qualitatively and quantitatively. Abstracting and indexing for Advanced Engineering Informatics include Science Citation Index Expanded, Scopus and INSPEC.