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Structure from motion (SFM) is a methodology for automatically reconstructing three-dimensional (3D) models from a series of two-dimensional (2D) images when there is no a priori knowledge of the camera location and direction. Modern unmanned aerial vehicles (UAV) now provide a low-cost means of obtaining aerial video footage of a point of interest. Unfortunately, raw video lacks the required information for SFM software, as it does not record exchangeable image file (EXIF) information for the frames. In this work, a solution is presented to modify aerial video so that it can be used for photogrammetry. The paper then examines how the field of view effects the quality of the reconstruction. The input is unstabilized, and distorted video footage obtained from a low-cost UAV which is then combined with an open-source SFM system to reconstruct a 3D model. This approach creates a high quality reconstruction by reducing the amount of unknown variables, such as focal length and sensor size, while increasing the data density. The experiments conducted examine the optical field of view settings to provide sufficient overlap without sacrificing image quality or exacerbating distortion. The system costs less than e1000, and the results show the ability to reproduce 3D models that are of centimeter-level accuracy. For verification, the results were compared against millimeter-level accurate models derived from laser scanning.

3D Reconstructions Using Unstabilized Video Footage from an Unmanned Aerial Vehicle