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dc.contributor.authorByrne, Jonathan-
dc.contributor.authorO'Keeffe, Evan-
dc.contributor.authorLennon, Donal-
dc.identifier.citationByrne, J.; O'Keeffe, E.; Lennon, D.; Laefer, D.F. 3D Reconstructions Using UnstabilizedVideo Footage from an Unmanned Aerial Vehicle. J. Imaging 2017, 3, 15.ven
dc.description.abstractStructure 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.en
dc.description.sponsorshipEuropean Union Grant FP7-632227; IRC Grant GOIPD/2015/125; IRC Grant GOIPG/2015/3003, Geological Survey of Ireland Grant 2015-sc-Laefer; Science Foundation Ireland Grant 13/TIDA/I274en
dc.rightsThis item is published in an open access journal (MDPI J. Imaging) which encourages authors to self-archive articles in open repositories. The authors also retain all copyright for this material.en
dc.subjectunmanned aerial vehiclesen
dc.subjectremote sensingen
dc.subjecturban modelingen
dc.subjectaerial remote sensingen
dc.subjectstructure from motionen
dc.subject3D modelen
dc.subjectaerial videoen
dc.title3D Reconstructions Using Unstabilized Video Footage from an Unmanned Aerial Vehicleen
prism.publicationNameJournal of Imagingen
Appears in Collections:Debra Laefer's Collection

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