Design of an Automated System for the Retrieval of Emotional Content in Natural Images

dc.contributor.advisorSheth, Bhavin R.
dc.contributor.committeeMemberHan, Zhu
dc.contributor.committeeMemberNguyen, Hien Van
dc.contributor.committeeMemberStevenson, Scott B.
dc.contributor.committeeMemberHernandez, Arturo E.
dc.creatorAmbati, Saikiran
dc.date.accessioned2018-11-30T15:47:43Z
dc.date.available2018-11-30T15:47:43Z
dc.date.createdMay 2018
dc.date.issued2018-05
dc.date.submittedMay 2018
dc.date.updated2018-11-30T15:47:43Z
dc.description.abstractEmotions often drive us and our behaviors. An ability to reliably and automatically estimate the degree and kind of emotion aroused in a typical individual has widespread applicability. Two dimensions of emotion are key: arousal, or the extent to which a scene excites/calms and its valence, i.e. the extent to which it is pleasant/unpleasant. Past attempts to automate emotion detection in images have failed. Here, we adopt a hybrid, integrated approach that broadly consists of two components: a front-end consisting of a bank of classifiers that recognize the presence of specific semantic content (e.g. person/animal/beach) in the image; a back-end that weights the importance of each semantic category to generate a discrete output of image valence and arousal. Model performance was compared with ground truth, i.e. ratings provided by human subjects: test accuracy was 96.0% on valence (chance=50%) and 92.0% on arousal classification (chance=33%) across the externally validated image set.
dc.description.departmentElectrical and Computer Engineering, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10657/3437
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectEmotion capture
dc.subjectArousal
dc.subjectValence
dc.titleDesign of an Automated System for the Retrieval of Emotional Content in Natural Images
dc.type.dcmiText
dc.type.genreThesis
local.embargo.lift2020-05-01
local.embargo.terms2020-05-01
thesis.degree.collegeCullen College of Engineering
thesis.degree.departmentElectrical and Computer Engineering, Department of
thesis.degree.disciplineElectrical Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelMasters
thesis.degree.nameMaster of Science in Electrical Engineering

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