Applications of Factorization Theorem and Ontologies for Activity ModelingRecognition and Anomaly Detection

dc.contributor.advisorChellappa, Ramaen_US
dc.contributor.authorAkdemir, Umuten_US
dc.contributor.departmentComputer Scienceen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.description.abstractIn this thesis two approaches for activity modeling and suspicious activity detection are examined. First is application of factorization theorem extension for deformable models in two dierent contexts. First is human activity detection from joint position information, and second is suspicious activity detection for tarmac security. It is shown that the first basis vector from factorization theorem is good enough to dierentiate activities for human data and to distinguish suspicious activities for tarmac security data. Second approach dierentiates individual components of those activities using semantic methodol- ogy. Although currently mainly used for improving search and information retrieval, we show that ontologies are applicable to video surveillance. We evaluate the domain ontologies from Challenge Project on Video Event Taxonomy sponsored by ARDA from the perspective of general ontology design principles. We also focused on the eect of the domain on the granularity of the ontology for suspicious activity detection.en_US
dc.format.extent1080856 bytes
dc.subject.pqcontrolledComputer Scienceen_US
dc.subject.pquncontrolledvideo surveillanceen_US
dc.subject.pquncontrolledfactorization theoremen_US
dc.subject.pquncontrolleddeformable modelsen_US
dc.subject.pquncontrolledsemantic knowledgeen_US
dc.subject.pquncontrolledactivity recognitionen_US
dc.titleApplications of Factorization Theorem and Ontologies for Activity ModelingRecognition and Anomaly Detectionen_US


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