Unmanned aerial vehicle (UAV) images have gained extensive attention in varying fields, and the Structure from Motion (SfM) technique has become the gold standard for aerial triangulation of UAV images. With increasing data volume caused by the use of multi-view and high-resolution imaging systems and the enhancement of UAV platform’s endurance, the capability for orientation of large-scale UAV images is becoming a prominent and necessary feature for SfM-based solutions. A classical SfM pipeline consists of three major steps, i.e., (i) feature extraction for an individual image, (ii) feature matching for each image pair, and (iii) parameter solving based on iterative bundle adjustment. Most of the time costs are consumed in the second and third steps. This can be explained from three main aspects. First, for feature matching the large number of images and high overlapping degrees cause high combinational complexity of match pairs. Second, the efficiency of commonly utilized techniques for outlier removal would be seriously degenerated because of high outlier ratios of initial matches. Third, for parameter solving of camera poses and scene structures, the iterative execution of bundle adjustment (BA) leads to high computational costs in the incremental SfM workflow. Thus, this paper gives a systematic survey of the state-of-the-art for match pair selection from both ordered and unordered datasets, for outlier removal of initial matches dominated by outliers, and for efficiency improvement of BA, and conducts an experimental evaluation for six well-known SfM-based software packages on UAV image orientation.

无人机（UAV）图像已在各个领域引起了广泛关注，并且“运动结构（SfM）”技术已成为无人机图像三角测量的金标准。由于使用多视图和高分辨率成像系统而导致的数据量增加以及无人机平台的耐用性增强，面向大型无人机图像的定向能力正成为基于SfM的解决方案的重要且必要的功能。经典的SfM流水线包括三个主要步骤，即（i）对单个图像进行特征提取，（ii）对每个图像对进行特征匹配，以及（iii）基于迭代束调整的参数求解。在第二和第三步中消耗了大部分时间成本。这可以从三个主要方面进行解释。第一，对于特征匹配而言，大量图像和高重叠度会导致匹配对的高组合复杂度。其次，由于初始匹配的异常值比率很高，因此，广泛使用的异常值消除技术的效率将大大降低。第三，对于摄像机姿势和场景结构的参数求解，捆绑调整（BA）的迭代执行导致增量SfM工作流程中的计算成本较高。因此，本文对从有序和无序数据集中选择匹配对，从异常值中脱颖而出的初始匹配值进行异常值去除以及提高BA效率等方面进行了系统的研究，并进行了实验评估六个关于无人机图像方向的著名的基于SfM的软件包。