Using image features and eye tracking device to predict human emotions towards abstract images

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dc.contributor.authorPasupa, Kitsuchart
dc.contributor.authorChatkamjuncharoen, Panawee
dc.contributor.authorWuttilertdeshar, Chotiros
dc.contributor.authorSugimoto, Masanori
dc.date.accessioned2026-08-06T10:13:02Z
dc.date.available2026-08-06T10:13:02Z
dc.date.issued2016-01-01
dc.description.abstractNowadays, emotional semantic image retrieval system enables users to access images that they want in a database according to emotional concept. This leads to affective image classification task which recently attracts researchers’ attention. However, different users may experience different emotions depending on where, in the image, they are gazing on. This paper presents an improved prediction method by taking into account the users eye movement as implicit feedback while they are looking at the image. Our experimental results show that using both eye movement information and image feature together to determine users emotion gave more accurate predictions than using image feature alone.
dc.identifier.citationLecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 9431, 419-430, 2016
dc.identifier.doi10.1007/978-3-319-29451-3_34
dc.identifier.issn03029743
dc.identifier.other2-s2.0-84959010843
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/6659
dc.sourceLecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics
dc.subjectEmotion
dc.subjectEye movements
dc.subjectImage retrieval
dc.subjectImplicit feedback
dc.titleUsing image features and eye tracking device to predict human emotions towards abstract images
dc.typeConference Paper

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