Evolutionary Design for Computational Visual Attention

dc.contributor.authorBruce, Neilen
dc.date.accessioned2006-08-22T14:01:08Z
dc.date.available2006-08-22T14:01:08Z
dc.date.issued2003en
dc.date.submitted2003en
dc.description.abstractA new framework for simulating the visual attention system in primates is introduced. The proposed architecture is an abstraction of existing approaches influenced by the work of Koch and Ullman, and Tompa. Each stage of the attentional hierarchy is chosen with consideration for both psychophysics and mathematical optimality. A set of attentional operators are derived that act on basic image channels of intensity, hue and orientation to produce maps representing perceptual importance of each image pixel. The development of such operators is realized within the context of a genetic optimization. The model includes the notion of an information domain where feature maps are transformed to a domain that more closely corresponds to the human visual system. A careful analysis of various issues including feature extraction, density estimation and data fusion is presented within the context of the visual attention problem.en
dc.formatapplication/pdfen
dc.format.extent1113476 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10012/900
dc.language.isoenen
dc.pendingfalseen
dc.publisherUniversity of Waterlooen
dc.rightsCopyright: 2003, Bruce, Neil. All rights reserved.en
dc.subjectSystems Designen
dc.subjectvisual attentionen
dc.subjectgenetic algorithmsen
dc.subjectimage processingen
dc.subjectimage analysisen
dc.subjectinformation theoryen
dc.subjectlearning systemsen
dc.subjectmachine visionen
dc.subjectcognitive scienceen
dc.titleEvolutionary Design for Computational Visual Attentionen
dc.typeMaster Thesisen
uws-etd.degreeMaster of Applied Scienceen
uws-etd.degree.departmentSystems Design Engineeringen
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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