[论文解读] Optimized Views Photogrammetry: Precision Analysis and A Large-scale Case Study in Qingdao

Qingquan Li, Wenshuai Yu+1 more|arXiv (Cornell University)|Jun 24, 2022

Remote Sensing and LiDAR Applications被引用 5

一句话总结

本文提出了一种基于无人机的3D重建方法——优化视角摄影测量法，该方法利用粗略的城市模型生成并优化飞行轨迹，通过优先选择可重建性高的视角并最小化冗余。与传统的倾斜摄影测量法相比，该方法在遮挡严重的城市区域实现了3–5倍的精度提升，其有效性通过精度分析和在青岛的大规模案例研究得到验证。

ABSTRACT

UAVs have become one of the widely used remote sensing platforms and played a critical role in the construction of smart cities. However, due to the complex environment in urban scenes, secure and accurate data acquisition brings great challenges to 3D modeling and scene updating. Optimal trajectory planning of UAVs and accurate data collection of onboard cameras are non-trivial issues in urban modeling. This study presents the principle of optimized views photogrammetry and verifies its precision and potential in large-scale 3D modeling. Different from oblique photogrammetry, optimized views photogrammetry uses rough models to generate and optimize UAV trajectories, which is achieved through the consideration of model point reconstructability and view point redundancy. Based on the principle of optimized views photogrammetry, this study first conducts a precision analysis of 3D models by using UAV images of optimized views photogrammetry and then executes a large-scale case study in the urban region of Qingdao city, China, to verify its engineering potential. By using GCPs for image orientation precision analysis and TLS (terrestrial laser scanning) point clouds for model quality analysis, experimental results show that optimized views photogrammetry could construct stable image connection networks and could achieve comparable image orientation accuracy. Benefiting from the accurate image acquisition strategy, the quality of mesh models significantly improves, especially for urban areas with serious occlusions, in which 3 to 5 times of higher accuracy has been achieved. Besides, the case study in Qingdao city verifies that optimized views photogrammetry can be a reliable and powerful solution for the large-scale 3D modeling in complex urban scenes.

研究动机与目标

• 解决由于遮挡和无人机飞行路径不理想导致的复杂城市环境中数据质量低和3D模型不完整的问题。
• 通过优化无人机飞行路径和图像采集策略，提高大规模城市场景中3D重建的精度和完整性。
• 展示优化视角摄影测量法在真实世界大规模城市3D建模中的工程可行性与性能表现。
• 基于地面控制点（GCPs）和TLS点云，对比优化视角摄影测量法与经典倾斜摄影测量法的精度。

提出的方法

• 生成城市场景的初始粗略3D模型，以指导无人机飞行路径规划。
• 以模型点的可重建性和视角冗余度为约束条件，优化无人机飞行路径。
• 通过密集采样和迭代视角优化，确保图像采集的充分性和有效性。
• 利用GCPs进行图像定向，并通过相对与绝对定向指标验证精度。
• 使用配备25个节点的计算集群进行3D重建，以高效处理大规模数据。
• 通过将重建的网格模型与地面激光扫描（TLS）点云进行对比，验证模型质量。

实验结果

研究问题

• RQ1 优化视角摄影测量法是否能在复杂城市环境中构建稳定的图像连接网络？
• RQ2 优化视角摄影测量法的图像定向精度与经典倾斜摄影测量法相比如何？
• RQ3 优化视角摄影测量法在遮挡严重的城市区域中，对3D模型质量的提升程度如何？
• RQ4 在青岛的案例中，优化视角摄影测量法是否可有效扩展至大规模城市3D建模？
• RQ5 视角优化对高遮挡区域网格模型的完整性和精度有何影响？

主要发现

• 优化视角摄影测量法成功构建了稳定的图像连接网络，实现了复杂城市区域的可靠3D重建。
• 图像定向精度与经典倾斜摄影测量法相当，相对与绝对定向误差均处于可接受的工程容差范围内。
• 在遮挡严重的城市区域，优化视角摄影测量法的精度比传统方法高出3至5倍。
• 所生成的3D网格模型在细节和完整性方面均有显著提升，尤其体现在建筑立面和低能见度区域。
• 青岛的大规模案例研究证明，优化视角摄影测量法是城市3D建模中可靠且可扩展的解决方案。
• 该方法减少了开阔区域的冗余数据采集，同时确保了复杂遮挡区域的充分观测。