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dc.contributor.advisorWills, Linda
dc.contributor.advisorWills, Scott
dc.contributor.authorAzmat, Shoaib
dc.date.accessioned2015-09-21T15:52:24Z
dc.date.available2015-09-22T05:30:06Z
dc.date.created2014-08
dc.date.issued2014-06-19
dc.date.submittedAugust 2014
dc.identifier.urihttp://hdl.handle.net/1853/54005
dc.description.abstractThis dissertation presents an efficient multilayer background modeling approach to distinguish among midground objects, the objects whose existence occurs over varying time scales between the extremes of short-term ephemeral appearances (foreground) and long-term stationary persistences (background). Traditional background modeling separates a given scene into foreground and background regions. However, the real world can be much more complex than this simple classification, and object appearance events often occur over varying time scales. There are situations in which objects appear on the scene at different points in time and become stationary; these objects can get occluded by one another, and can change positions or be removed from the scene. Inability to deal with such scenarios involving midground objects results in errors, such as ghost objects, miss-detection of occluding objects, aliasing caused by the objects that have left the scene but are not removed from the model, and new objects’ detection when existing objects are displaced. Modeling temporal layers of multiple objects allows us to overcome these errors, and enables the surveillance and summarization of scenes containing multiple midground objects.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectVideo surveillance
dc.subjectMultilayer background modeling
dc.subjectAdaptive background modeling
dc.subjectTemporal multimodal mean
dc.subjectOcclusion reasoning
dc.subjectAppearance model
dc.subjectVideo summarization
dc.subjectLow-power integrated GPU
dc.subjectEmbedded smart camera
dc.subjectSpatio-temporal scene analysis
dc.titleMultilayer background modeling under occlusions for spatio-temporal scene analysis
dc.typeDissertation
dc.description.degreePh.D.
dc.contributor.departmentElectrical and Computer Engineering
dc.embargo.terms2015-08-01
thesis.degree.levelDoctoral
dc.contributor.committeeMemberHamblen, James
dc.contributor.committeeMemberHong, Bo
dc.contributor.committeeMemberLanterman, Aaron
dc.contributor.committeeMemberVetter, Jeffrey
dc.date.updated2015-09-21T15:52:24Z


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