Image Geolocation Through Hierarchical Classification and Dictionary-Based Recogntion

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dc.contributor.advisorChellappa, Ramaen_US
dc.contributor.authorJones, Michael Williamen_US
dc.contributor.departmentElectrical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2013-02-06T07:14:02Z
dc.date.available2013-02-06T07:14:02Z
dc.date.issued2012en_US
dc.description.abstractImage geolocation, estimating GPS coordinates from an image, is a relatively new endeavor in the field of computer vision. This thesis presents two approaches to obtain the coordinates: hierarchical and dictionary-based. The hierarchical approach uses SVMs to first determine the general environment of the image and then estimates the exact location within that environment. The dictionary-based approaches are performed with linear and non-linear dictionaries using K-SVD and KK-SVD. Both methods are performed on the image feature gist and histograms of the image's color, SIFT descriptors, textons, and lines. Both the hierarchical and dictionary-based approaches build upon and combine existing systems to provide improved accuracy on a data set of twelve locations belonging to four environmental types.en_US
dc.identifier.urihttp://hdl.handle.net/1903/13553
dc.subject.pqcontrolledElectrical engineeringen_US
dc.subject.pqcontrolledComputer scienceen_US
dc.subject.pqcontrolledComputer engineeringen_US
dc.subject.pquncontrolledComputer Visionen_US
dc.subject.pquncontrolledDictionariesen_US
dc.subject.pquncontrolledGeolocationen_US
dc.subject.pquncontrolledHierarchicalen_US
dc.subject.pquncontrolledPattern Recogntionen_US
dc.titleImage Geolocation Through Hierarchical Classification and Dictionary-Based Recogntionen_US
dc.typeThesisen_US

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