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dc.contributor.supervisor Bruce, Neil (Computer Science) en_US
dc.contributor.author Boisvert, Jonathan
dc.date.accessioned 2016-03-22T22:14:42Z
dc.date.available 2016-03-22T22:14:42Z
dc.date.issued 2015
dc.identifier.uri http://hdl.handle.net/1993/31168
dc.description.abstract In seminal work, Yarbus examined the characteristic scanpaths that result when viewing an image, observing that scanpaths varied significantly depending on the question posed to the observer. While early efforts examining this hypothesis were equivocal, it has since been established that aspects of an observer’s assigned task may be inferred from their gaze. In this thesis we examine two datasets that have not previously been considered involving prediction of task and observer sentiment respectively. The first of these involves predicting general tasks assigned to observers viewing images, and the other predicting subjective ratings recorded after viewing advertisements. The results present interesting observations on task groupings and affective dimensions of images, and the value of various measurements (gaze or image based) in making these predictions. Analysis also demonstrates the importance of how data is partitioned for predictive analysis, and the complementary nature of gaze specific and image derived features. en_US
dc.subject Vision en_US
dc.subject Gaze en_US
dc.subject Fixations en_US
dc.subject Eye movements en_US
dc.subject Yarbus en_US
dc.subject Visual search en_US
dc.subject Affective response en_US
dc.subject Task inference en_US
dc.title The eyes as a window to the mind: inferring cognitive state from gaze patterns en_US
dc.degree.discipline Computer Science en_US
dc.contributor.examiningcommittee Wang, Yang (Computer Science) Marotta, Jonathan (Psychology) en_US
dc.degree.level Master of Science (M.Sc.) en_US
dc.description.note May 2016 en_US


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