Person Identification From Audio and Visual Aesthetics

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dc.contributor.advisorGavrilova, Marina
dc.contributor.authorSieu, Brandon
dc.contributor.committeememberAi He, Helen
dc.contributor.committeememberZhao, Richard
dc.date2022-02
dc.date.accessioned2021-11-23T23:28:14Z
dc.date.available2021-11-23T23:28:14Z
dc.date.issued2021-11
dc.description.abstractIn recent years, the trend that allowed for person identiļ¬cation based on behavior rather than physical traits to emerge as a growing research domain. Its application spans areas such as online education, e-commerce, e-communication, human-computer interaction, robotics, and biometric security. The expression of opinions is an example of online behavior, that is commonly shared through the liking of images or music. A person's aesthetic preference involves using a person's sense of fondness to experienced stimulus. This thesis examines for the first time aesthetic preference as a biometric trait. It then establishes the efficacy of a combined multi-modal approach to person identification using aesthetic preference. The potency of this approach is tested on a proprietary dataset.en_US
dc.identifier.citationSieu, B. (2021). Person identification from audio and visual aesthetics (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/39401
dc.identifier.urihttp://hdl.handle.net/1880/114140
dc.language.isoengen_US
dc.publisher.facultyScienceen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectMachine Learningen_US
dc.subjectDeep Learningen_US
dc.subjectBehavioral Biometricsen_US
dc.subjectBiometric Securityen_US
dc.subjectVisual Aestheticsen_US
dc.subjectAudio Aestheticsen_US
dc.subjectPattern Recognitionen_US
dc.subject.classificationComputer Scienceen_US
dc.titlePerson Identification From Audio and Visual Aestheticsen_US
dc.typemaster thesisen_US
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameMaster of Science (MSc)en_US
ucalgary.item.requestcopytrueen_US
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