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dc.contributor.advisorDereniak, Eustaceen
dc.contributor.advisorFurenlid, Larsen
dc.contributor.authorZacherl, Walter David
dc.creatorZacherl, Walter Daviden
dc.date.accessioned2016-06-14T22:25:54Z
dc.date.available2016-06-14T22:25:54Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/10150/613145
dc.description.abstractA new method of registering multiple range datasets collected in a GPS-denied, tunnel-like environment is presented. The method is designed to function with minimal user inputs and be effective over a wide range of changes in observation angle. The method is initially developed to operate on data in a general 2.5D coordinate system. Then, the general registration method is specifically tailored to a 2.5D spherical coordinate system. To apply the method, the range data is first filtered with a series of discrete Gaussian-based filters to construct a second-order Taylor series approximation to the surface about each sampled point. Finally, principal curvatures are calculated and compared across neighboring datasets to determine homologies and the best fit transfer matrix. The new method relaxes the minimum change in perspective requirement between neighboring datasets typical of other algorithms. Results from the application of the method on both synthetic and real-world data are shown. The real-world data comes from a series of high explosive tests performed in a tunnel environment. The tunnels were oriented horizontally in rock and constructed with boring equipment. The tunnel surfaces were surveyed with a Faro Focus3D terrestrial panorama scanning light detection and ranging (lidar) system both before and after a high explosive device was detonated inside the tunnel with the intent of documenting damage to the tunnel surface.
dc.language.isoen_USen
dc.publisherThe University of Arizona.en
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en
dc.subjectlidaren
dc.subjectmedical imagingen
dc.subjectpattern recognitionen
dc.subjectregistrationen
dc.subjectremote sensingen
dc.subjectOptical Sciencesen
dc.subjectfeature extractionen
dc.titleMethod for Registering Lidar Data in Restrictive, Tunnel-Like Environmentsen_US
dc.typetexten
dc.typeElectronic Dissertationen
thesis.degree.grantorUniversity of Arizonaen
thesis.degree.leveldoctoralen
dc.contributor.committeememberClarkson, Ericen
dc.contributor.committeememberDereniak, Eustaceen
dc.contributor.committeememberFurenlid, Larsen
thesis.degree.disciplineGraduate Collegeen
thesis.degree.disciplineOptical Sciencesen
thesis.degree.namePh.D.en
refterms.dateFOA2018-06-18T10:24:11Z
html.description.abstractA new method of registering multiple range datasets collected in a GPS-denied, tunnel-like environment is presented. The method is designed to function with minimal user inputs and be effective over a wide range of changes in observation angle. The method is initially developed to operate on data in a general 2.5D coordinate system. Then, the general registration method is specifically tailored to a 2.5D spherical coordinate system. To apply the method, the range data is first filtered with a series of discrete Gaussian-based filters to construct a second-order Taylor series approximation to the surface about each sampled point. Finally, principal curvatures are calculated and compared across neighboring datasets to determine homologies and the best fit transfer matrix. The new method relaxes the minimum change in perspective requirement between neighboring datasets typical of other algorithms. Results from the application of the method on both synthetic and real-world data are shown. The real-world data comes from a series of high explosive tests performed in a tunnel environment. The tunnels were oriented horizontally in rock and constructed with boring equipment. The tunnel surfaces were surveyed with a Faro Focus3D terrestrial panorama scanning light detection and ranging (lidar) system both before and after a high explosive device was detonated inside the tunnel with the intent of documenting damage to the tunnel surface.


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