本文为美国德克萨斯A&M大学（作者：MICHAEL SCHWIND）的硕士论文，共129页。

运动重构（SfM）是一种摄影测量技术，通过重叠的二维图像序列估计三维结构。该技术在计算机视觉领域进行了研究，并应用于考古学、工程学和地球科学等领域。目前，存在许多支持生成三维点云的SfM软件包。关于这些软件生成的地形数据在不同地形类型上是如何不同的，以及为什么它们可能产生不同的结果，目前还没有进行太多的研究。本项工作旨在比较和描述三种不同SfM软件包所产生的点云之间的差异：两种著名的商业专业软件（Pix4D、AgisoftPhotoScan）和一种开源软件（OpenDroneMap）。

使用DJI幻影3专业小型无人驾驶飞机系统（sUAS）对五种地形类型进行成像，这些地形类型包括沼泽环境、略微倾斜的沙滩和码头、森林覆盖的半岛、房屋和平坦的停车场。每一组图像都用每种软件进行处理，然后直接相互比较。在处理图像集之前，对软件设置进行分析和选择，以允许在三种软件中进行最相似的设置。这样做是为了尽量减少由不同设置引起的点云差异，然后比较了不同软件合成点云的特征。此外，使用Riegl VZ-400扫描仪对平坦停车场进行了地面激光探测和测距（LiDAR）。这些数据作为地面的真实情况，以便对sUAS-SfM点云进行准确评估。不同合成结果之间存在差异，不仅在云特征上表现明显，而且在精度上也很明显。

本项研究使SfM摄影测量的用户能够更好地了解不同处理软件之间的比较以及SfM自动化在三维重建中的固有敏感特性。由于本研究主要使用软件中的默认设置，因此进一步研究参数变化对不同SfM软件包生成的点云数据集保真度的影响将是有益的。

Structure from Motion (SfM) is aphotogrammetric technique whereby three-dimensional structures (3D) areestimated from overlapping two-dimensional (2D) image sequences. It is studiedin the field of computer vision and utilized in fields such as archeology,engineering, and the geosciences. Currently, many SfM software packages existthat allow for the generation of 3D point clouds. Little work has been done toshow how topographic data generated from these software differ over varyingterrain types and why they might produce different results. This work aims tocompare and characterize the differences between point clouds generated bythree different SfM software packages: two well-known proprietary solutions(Pix4D, Agisoft PhotoScan) and one open source solution (OpenDroneMap). Five terraintypes were imaged utilizing a DJI Phantom 3 Professional small unmanned aircraftsystem (sUAS). These terrain types include a marsh environment, a gently slopedsandy beach and jetties, a forested peninsula, a house, and a flat parking lot.Each set of imagery was processed with each software and then directly comparedto each other. Before processing the sets of imagery, the software settingswere analyzed and chosen in a manner that allowed for the most similar settingsto be set across the three software types. This was done in an attempt to minimizepoint cloud differences caused by dissimilar settings. The characteristics ofthe resultant point clouds were then compared with each other. Furthermore, aterrestrial light detection and ranging (LiDAR) survey was conducted over theflat parking lot using a Riegl VZ-400 scanner. This data served as ground truthin order to conduct an accuracy assessment of the sUAS-SfM point clouds.Differences were found between the different results, apparent not only in thecharacteristics of the clouds, but also the accuracy. This study allows forusers of SfM photogrammetry to have a better understanding of how differentprocessing software compare and the inherent sensitivity of SfM automation in3D reconstruction. Because this study used mostly default settings within thesoftware, it would be beneficial for further research to investigate theeffects of changing parameters have on the fidelity of point cloud datasetsgenerated from different SfM software packages.

1 引言

2 文献回顾

3 研究范围与数据集

4 研究方法

5 结果与讨论

6 结论

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