HUMAN APPEARANCE MODELING IN VISUAL SURVEILLANCE

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dc.contributor.advisorChellapa, Ramaen_US
dc.contributor.authorYu, Yangen_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.accessioned2007-09-28T15:01:57Z
dc.date.available2007-09-28T15:01:57Z
dc.date.issued2007-08-07en_US
dc.description.abstractWe present an appearance model for establishing correspondence between tracks of people which may be taken at different places, at different times or across different cameras. Illumination insensitive color features, i.e., RGB rank feature and brightness-color feature are used. Path-length feature is added for structural information and invariance to motion and pose. The appearance model is constructed by kernel density estimation. Kullback-Leibler distance measures the similarity between the models. To further exploit the information in video sequence, key frame selection method and online hierarchical clustering algorithm are proposed to construct appearance model from video. Key frame selection use the frames with large information gain to represent the appearance model. Online hierarchical clustering algorithm condense the model into a few clusters in the framework of our appearance model. Experimental results demonstrate the important role of the path-length feature in the appearance model and the effectiveness of the proposed appearance model and matching method.en_US
dc.format.extent929239 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/7354
dc.language.isoen_US
dc.subject.pqcontrolledEngineering, Electronics and Electricalen_US
dc.subject.pquncontrolledappearance modelingen_US
dc.subject.pquncontrolledpath-lengthen_US
dc.subject.pquncontrolledKullback-Leibler distanceen_US
dc.subject.pquncontrolledkey frame selectionen_US
dc.subject.pquncontrolledonline clusteringen_US
dc.subject.pquncontrolledhierarchical clusteringen_US
dc.titleHUMAN APPEARANCE MODELING IN VISUAL SURVEILLANCEen_US
dc.typeThesisen_US

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