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Spatial Bayesian surprise for image saliency and quality assessment

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dc.contributor.author Gkioulekas, I en
dc.contributor.author Evangelopoulos, G en
dc.contributor.author Maragos, P en
dc.date.accessioned 2014-03-01T02:47:00Z
dc.date.available 2014-03-01T02:47:00Z
dc.date.issued 2010 en
dc.identifier.issn 15224880 en
dc.identifier.uri http://hdl.handle.net/123456789/32981
dc.subject Bayesian surprise en
dc.subject Image quality assessment en
dc.subject Image saliency en
dc.subject Region detection en
dc.subject Visual attention en
dc.subject.other Bayesian en
dc.subject.other Image quality assessment en
dc.subject.other Image saliency en
dc.subject.other Region detection en
dc.subject.other Visual Attention en
dc.subject.other Bayesian networks en
dc.subject.other Image quality en
dc.subject.other Imaging systems en
dc.subject.other Rating en
dc.subject.other Tracking (position) en
dc.title Spatial Bayesian surprise for image saliency and quality assessment en
heal.type conferenceItem en
heal.identifier.primary 10.1109/ICIP.2010.5650991 en
heal.identifier.secondary http://dx.doi.org/10.1109/ICIP.2010.5650991 en
heal.identifier.secondary 5650991 en
heal.publicationDate 2010 en
heal.abstract We propose an alternative interpretation of Bayesian surprise in the spatial domain, to account for saliency arising from contrast in image context. Our saliency formulation is integrated in three different application scenaria, with considerable improvements in performance: 1) visual attention prediction, validated using eye- and mouse-tracking data, 2) region of interest detection, to improve scale selection and localization, 3) image quality assessment to achieve better agreement with subjective human evaluations. © 2010 IEEE. en
heal.journalName Proceedings - International Conference on Image Processing, ICIP en
dc.identifier.doi 10.1109/ICIP.2010.5650991 en
dc.identifier.spage 1081 en
dc.identifier.epage 1084 en


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