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dc.contributor.advisorSamuel Madden.en_US
dc.contributor.authorBastani, Favyenen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2018-09-17T15:55:37Z
dc.date.available2018-09-17T15:55:37Z
dc.date.copyright2018en_US
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/118057
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 63-65).en_US
dc.description.abstractCreating and updating road maps is currently an expensive and often manual process, and thus maps today are outdated or have poor coverage in large regions of the world. Automatically inferring the road network graph from aerial imagery provides a promising avenue to reducing the cost of maintaining road maps, but existing inference methods have poor precision. This thesis develops a novel iterative graph construction process for extracting graph structures from images, and applies this process to automatic road topology inference to significantly reduce error rates.en_US
dc.description.statementofresponsibilityby Favyen Bastani.en_US
dc.format.extent65 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleRobust road topology extraction from aerial imageryen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc1051460450en_US


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