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dc.contributor.advisorEspy-Wilson, Carol Y.en_US
dc.contributor.authorKibey, Sameer Avinashen_US
dc.date.accessioned2007-06-22T05:31:44Z
dc.date.available2007-06-22T05:31:44Z
dc.date.issued2007-02-20
dc.identifier.urihttp://hdl.handle.net/1903/6697
dc.description.abstractIn this Thesis, we focus on problems in surveillance video analysis and propose advanced metadata modeling techniques to address them. First, we explore the problem of constructing a snapshot summary of people in a video sequence. We propose an algorithm based on the eigen-analysis of faces and present an evaluation of the method. Second, we present an algorithm to learn occlusion points in a scene using long observations of moving objects, provide an implementation and evaluate its performance. Third, to address the problem of availability and storage of surveillance videos, we propose a novel methodology to simulate video metadata. The technique is completely automated and can generate metadata for any scenario with minimal user interaction. Finally, a threat detection model using activity analysis and trajectory data of moving objects is proposed and implemented. The collection of tools presented in this Thesis provides a basis for higher level video analysis algorithms.en_US
dc.format.extent8782378 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.titleTools for Advanced Video Metadata Modelingen_US
dc.typeThesisen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentElectrical Engineeringen_US
dc.subject.pqcontrolledEngineering, Electronics and Electricalen_US


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