Handling uncertainty in video analysis with spatiotemporal visual attention

Rapantzikos, K; Avrithis, Y; Kollias, S

dc.contributor.author	Rapantzikos, K	en
dc.contributor.author	Avrithis, Y	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T02:43:21Z
dc.date.available	2014-03-01T02:43:21Z
dc.date.issued	2005	en
dc.identifier.issn	10987584	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31354
dc.subject	Computer Vision	en
dc.subject	Scene Understanding	en
dc.subject	Video Analysis	en
dc.subject	Visual Attention	en
dc.subject.other	Classification (of information)	en
dc.subject.other	Computer vision	en
dc.subject.other	Eye movements	en
dc.subject.other	Image segmentation	en
dc.subject.other	Vision	en
dc.subject.other	Visual communication	en
dc.subject.other	Natural vision	en
dc.subject.other	Spatiotemporal information	en
dc.subject.other	Video analysis	en
dc.subject.other	Visual attention (VA)	en
dc.subject.other	Video signal processing	en
dc.title	Handling uncertainty in video analysis with spatiotemporal visual attention	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/FUZZY.2005.1452395	en
heal.identifier.secondary	http://dx.doi.org/10.1109/FUZZY.2005.1452395	en
heal.publicationDate	2005	en
heal.abstract	In natural vision, we center our fixation on the most informative points in a scene in order to reduce our overall uncertainty about the scene and help interpret it. Even if we are looking for a specific stimulus around us, we face a great amount of uncertainty since that stimulus could be in any spatial location. Visual attention (VA) schemes have been proposed by researchers to account for the ability of the human eye to quickly fixate on informative regions. Recently, VA in images, and especially saliency-based VA, became an active research topic of the computer vision community. The proposed work provides an extension towards VA in video sequences by integrating spatiotemporal information. The potential applications include video classification, scene understanding, surveillance and segmentation. © 2005 IEEE.	en
heal.journalName	IEEE International Conference on Fuzzy Systems	en
dc.identifier.doi	10.1109/FUZZY.2005.1452395	en
dc.identifier.spage	213	en
dc.identifier.epage	217	en