Scene information guided aerial photogrammetric mission recomposition towards detailed level building reconstruction

• Published in: Advanced engineering informatics 2024-10, Vol.62, p.102913, Article 102913
• Main Authors: Akbar, Akram, Liu, Chun, Wu, Hangbin, Jia, Shoujun, Xu, Zeran
• Format: Article
• Language: English
• Subjects: Detailed-level real 3D model; Mission recomposition; Photogrammetric 3D reconstruction; Reconstruction quality assessment; UAV path planning
• ISSN: 1474-0346
• DOI: 10.1016/j.aei.2024.102913

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.