ABSTRACT 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.

中文翻译：

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从连续倾斜无人机系统 (UAS) 图像中提取三维 (3D) 空间信息以进行数字表面建模

摘要 无人机系统 (UAS) 的出现促使近距离图像成为使空间应用多样化的普遍来源。除了天底场景，UAS 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。这些图像为在三维 (3D) 中更完整地重建地表提供了更多可能性。然而，由于通过直接地理配准测量的不稳定和/或未知的外部方向参数 (EOP)，处理用于 3D 建模的 UAS 图像多年来一直是一项具有挑战性的任务。对于 EOP 不足或缺失的连续倾斜 UAS 图像，本文尝试从这些类型的图像中提取 3D 空间信息以实现数字表面重建。提出了在相对空间中集成相机 EOP 恢复和 3D 重建的模块化工作流程。这些图像通过基于特征的运动增量结构 (fi-SfM) 在空间上相关，用于定位、立体对选择和修改。此后，数字表面重建将通过基于 fi-SfM 的结果的密集匹配和空间交叉来解决。实验结果表明，设计的模式在估计相机 EOP 和修改不合适的图像对以改进 3D 重建方面是一致的。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）。完整性评估验证了大部分地表可以成功获得90%以上，