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dc.contributor.authorKIMURA, Akisatoen
dc.contributor.authorYONETANI, Ryoen
dc.contributor.authorHIRAYAMA, Takatsuguen
dc.contributor.alternative木村, 昭悟ja
dc.contributor.alternative米谷, 竜ja
dc.contributor.alternative平山, 高嗣ja
dc.date.accessioned2013-03-15T02:36:45Z-
dc.date.available2013-03-15T02:36:45Z-
dc.date.issued2013-03-
dc.identifier.issn0916-8532-
dc.identifier.urihttp://hdl.handle.net/2433/171749-
dc.description.abstractWe humans are easily able to instantaneously detect the regions in a visual scene that are most likely to contain something of interest. Exploiting this pre-selection mechanism called visual attention for image and video processing systems would make them more sophisticated and therefore more useful. This paper briefly describes various computational models of human visual attention and their development, as well as related psychophysical findings. In particular, our objective is to carefully distinguish several types of studies related to human visual attention and saliency as a measure of attentiveness, and to provide a taxonomy from several viewpoints such as the main objective, the use of additional cues and mathematical principles. This survey finally discusses possible future directions for research into human visual attention and saliency computation.en
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherIEICEen
dc.rights© 2013 IEICE.en
dc.subjecthuman visual attentionen
dc.subjectcomputational modelen
dc.subjectsaliencyen
dc.subjectbottom-upen
dc.subjecttop-downen
dc.titleComputational Models of Human Visual Attention and Their Implementations: A Surveyen
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.ncidAA10826272-
dc.identifier.jtitleIEICE Transactions on Information and Systemen
dc.identifier.volumeE96-D-
dc.identifier.issue3-
dc.identifier.spage562-
dc.identifier.epage578-
dc.relation.doi10.1587/transinf.e96.d.562-
dc.textversionpublisher-
dc.relation.urlhttp://search.ieice.org/index.html-
dcterms.accessRightsopen access-
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