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dc.contributor.advisorWonka, Peter
dc.contributor.authorZhu, Peihao
dc.date.accessioned2019-06-11T10:50:14Z
dc.date.available2019-06-11T10:50:14Z
dc.date.issued2019-06
dc.identifier.doi10.25781/KAUST-806Z4
dc.identifier.urihttp://hdl.handle.net/10754/655517
dc.description.abstractWe present a system to extract architectural assets from large scale collections of panoramic imagery. First, we automatically rectify and crop parts of the panoramic image that contain dominant planes. Second, we use object detection to extract assets such as facades and windows. Third, we use various tools to determine attributes of the assets to determine the asset quality and index the assets for search. Fourth, we provide a user interface to visualize and query assets. Finally, we present applications to urban modeling and texture synthesis.
dc.language.isoen
dc.subjectAsset Extraction
dc.subjectUrban Modelling
dc.subjectobject Detection
dc.subjectClustering
dc.subjectSemantic Segmentation
dc.titleLarge Scale Architectural Asset Extraction from Panoramic Imagery
dc.typeThesis
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
thesis.degree.grantorKing Abdullah University of Science and Technology
dc.contributor.committeememberGhanem, Bernard
dc.contributor.committeememberTegner, Jesper
thesis.degree.disciplineComputer Science
thesis.degree.nameMaster of Science
refterms.dateFOA2019-06-11T10:50:15Z
kaust.request.doiyes


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