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dc.contributor.advisorDeSouza, Guilhermeeng
dc.contributor.authorHan, Kyung Min, 1976-eng
dc.date.issued2010eng
dc.date.submitted2010 Summereng
dc.descriptionTitle from PDF of title page (University of Missouri--Columbia, viewed on August 30, 2010).eng
dc.descriptionThe entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.eng
dc.descriptionDissertation advisor: Dr. Guilherme N. DeSouza.eng
dc.descriptionVita.eng
dc.descriptionPh. D. University of Missouri--Columbia 2010.eng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The task of geolocating targets from airborne video is required for many applications in surveillance, law enforcement, reconnaissance, etc. The usual approaches to target geolocation involve terrain data, single target tracking, gimbal control of camera heads, altimeters, etc. The main goal of this research is to eliminate those requirements and still develop an accurate, efficient, and robust vision-based method for geolocation that can be carried out for multiple targets simultaneously. In that sense, our main contributions to the state-of-the-art in geolocation are fourfold: 1) to eliminate the requirement for gimbal control of the cameras or any particular path planning control for the UAV; 2) to perform instaneous geolocation of multiple targets; 3) to eliminate the requirements for geo-referenced terrain database (elevation maps) or for an altimeter that provides the UAV's and target's altitudes; and 4) to use one single camera while still maintaining good overall accuracy. In order to achieve that, the only requirements for our proposed method are: that the intrinsic parameters of the camera be known; that the on board camera be equipped with global positioning system (GPS) and inertial measurement unit (IMU); and that the height of the vehicle can be calculated using feature points extracted from the ground surrounding the image of the targets. To satisfy the first two requirements, we developed and tested a robust calibration procedure that can estimate not only the intrinsic parameters of the camera, but also the IMU-camera parameters(also know in the robotic circles as the hand-eye calibration). The last requirement was addressed using a pseudo-stereo vision technique that maximizes the distance between stereo pairs (baseline)while keeping large the number of common feature points extracted by the algorithm.eng
dc.description.bibrefIncludes bibliographical references.eng
dc.format.extentxiv, 118 pageseng
dc.identifier.merlinb80593549eng
dc.identifier.oclc678599293eng
dc.identifier.urihttps://doi.org/10.32469/10355/9011eng
dc.identifier.urihttps://hdl.handle.net/10355/9011
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcollectionUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsAccess is limited to the campus of the University of Missouri-Columbia.eng
dc.subject.lcshAerial videographyeng
dc.subject.lcshGlobal Positioning Systemeng
dc.subject.lcshTarget acquisitioneng
dc.subject.lcshDrone aircraft -- Control systemseng
dc.subject.lcshInertial navigation (Aeronautics)eng
dc.titleTarget geolocation from airborne video without terrain dataeng
dc.typeThesiseng
thesis.degree.disciplineElectrical and computer engineering (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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