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dc.contributor.authorSchwind, Michael
dc.date.accessioned2017-03-14T21:52:28Z
dc.date.available2017-03-14T21:52:28Z
dc.date.issued2016-12
dc.identifier.urihttp://hdl.handle.net/1969.6/1137
dc.descriptionA thesis Submitted in Partial Fulfillment of the Requirements for the Degree of MASTER of SCIENCE in GEOSPATIAL SURVEYING ENGINEERING from Texas A&M University-Corpus Christi in Corpus Christi, Texas.en_US
dc.description.abstractStructure from Motion (SfM) is a photogrammetric technique whereby three-dimensional structures (3D) are estimated from overlapping two-dimensional (2D) image sequences. It is studied in the field of computer vision and utilized in fields such as archeology, engineering, and the geosciences. Currently, many SfM software packages exist that allow for the generation of 3D point clouds. Little work has been done to show how topographic data generated from these software differ over varying terrain types and why they might produce different results. This work aims to compare and characterize the differences between point clouds generated by three different SfM software packages: two well-known proprietary solutions (Pix4D, Agisoft PhotoScan) and one open source solution (OpenDroneMap). Five terrain types were imaged utilizing a DJI Phantom 3 Professional small unmanned aircraft system (sUAS). These terrain types include a marsh environment, a gently sloped sandy 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 compared to each other. Before processing the sets of imagery, the software settings were analyzed and chosen in a manner that allowed for the most similar settings to be set across the three software types. This was done in an attempt to minimize point cloud differences caused by dissimilar settings. The characteristics of the resultant point clouds were then compared with each other. Furthermore, a terrestrial light detection and ranging (LiDAR) survey was conducted over the flat parking lot using a Riegl VZ- 400 scanner. This data served as ground truth in order to conduct an accuracy assessment of the sUAS-SfM point clouds. Differences were found between the different results, apparent not only in the characteristics of the clouds, but also the accuracy. This study allows for users of SfM photogrammetry to have a better understanding of how different processing software compare and the inherent sensitivity of SfM automation in 3D reconstruction. Because this study used mostly default settings within the software, it would be beneficial for further research to investigate the effects of changing parameters have on the fidelity of point cloud datasets generated from different SfM software packages.en_US
dc.language.isoen_USen_US
dc.rightsThis material is made available for use in research, teaching, and private study, pursuant to U.S. Copyright law. The user assumes full responsibility for any use of the materials, including but not limited to, infringement of copyright and publication rights of reproduced materials. Any materials used should be fully credited with its source. All rights are reserved and retained regardless of current or future development or laws that may apply to fair use standards. Permission for publication of this material, in part or in full, must be secured with the author and/or publisher.en_US
dc.subjectLidaren_US
dc.subjectPoint clouden_US
dc.subjectquadcopteren_US
dc.subjectstructure from motionen_US
dc.subjectsurveyingen_US
dc.subjectunmanned aerial vehicleen_US
dc.titleComparing and characterizing three-dimensional point clouds derived by structure from motion photogrammetryen_US
dc.typeTexten_US
thesis.degree.disciplineGeospatial Surveying Engineeringen_US
thesis.degree.grantorTexas A & M University--Corpus Christien_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
dc.description.departmentComputing Sciencesen_US
dc.description.collegeCollege of Science and Engineeringen_US
dc.type.genreThesisen_US


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