Extracting three-dimensional (3D) spatial information from sequential oblique unmanned aerial system (UAS) imagery for digital surface modeling
Extracting three-dimensional (3D) spatial information from sequential oblique unmanned aerial system (UAS) imagery for digital surface modeling
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DOI：
10.1080/01431161.2020.1842538
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发表时间：
2020-11-19
影响因子：
3.4
通讯作者：
Matsuoka, Masashi
中科院分区：
文献类型：
--
作者：
Cheng, Min-Lung;Matsuoka, Masashi
随着无人机的出现，近距离遥感影像成为空间应用多样化的重要来源。除了最低点场景外，无人机系统还能够拍摄倾斜图像，这增加了从不同视角获取复杂空间信息的机会。这些图像提供了更多的可能性，以三维（3D）更完整地重建土地表面。然而，多年来，由于通过直接地理参考测量的不稳定和/或未知的外部定向参数（EOP），处理用于3D建模的UAS图像一直是一项具有挑战性的任务。针对连续倾斜UAS图像中EOP不足或缺失的情况，本文尝试从这些类型的图像中提取三维空间信息，实现数字表面重建。一个模块化的工作流程集成恢复相机EOP和三维重建在一个相对的空间。这些图像在空间上相关的基于特征的增量结构从运动（fi-SfM）的定位，立体对的选择和修改。在fi-SfM结果的基础上，通过稠密匹配和空间求交实现了数字曲面重构。实验结果表明，所设计的方案是一致的，估计相机的EOP和修改不适当的图像对，以改善三维重建。此外，由离散立体对生成的表面模型可以自动合并，以呈现完整的数字表面模型（DSM）。完整性评估证实，大部分的土地表面可以成功地获得超过90%，精度小于1（m），表明所实施的工作流程可以有效地实现三维建模。
The advent of unmanned aerial system (UAS) has prompted close-range imagery a prevalent source to diversify spatial applications. In addition to nadir scenes, UAS is able to take oblique imagery, which increases the opportunity to acquire sophisticated spatial information from different viewing angles. These images provide more possibilities to reconstruct the land surfaces more completely in three-dimensions (3D). However, dealing with UAS imagery for 3D modelling has been a challenging task for years due to unstable and/or unknown exterior orientation parameters (EOPs) measured by direct georeferencing. With sequential oblique UAS imagery with inadequate or missing EOPs, this paper attempts to extract 3D spatial information from these types of images to achieve digital surface reconstruction. A modular workflow integrating the recovery of camera EOPs and 3D reconstruction in a relative space is presented. These images are spatially related by a feature-based incremental structure-from-motion (fi-SfM) for localization, stereo pairs selection and modification. Digital surface reconstruction, thenceforth, is addressed through dense matching and space intersection upon the outcomes of fi-SfM. The experimental results show that the designed schema is coherent in estimating the camera EOPs and modifying the inappropriate image pairs for improved 3D reconstruction. Furthermore, the surface model generated by discrete stereo pairs can be merged automatically to present a complete digital surface model (DSM). The completeness assessment has verified that the majority of the land surface can be successfully obtained by more than 90%, and the accuracy less than 1 (m) indicates that the implemented workflow can be used to achieve 3D modelling effectively.