Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/100593
DC FieldValueLanguage
dc.contributor.authorAssunção, Gustavo-
dc.contributor.authorPatrão, Bruno-
dc.contributor.authorMenezes, Paulo-
dc.date.accessioned2022-07-06T08:41:19Z-
dc.date.available2022-07-06T08:41:19Z-
dc.date.issued2022-
dc.identifier.issn2626-8493pt
dc.identifier.urihttp://hdl.handle.net/10316/100593-
dc.description.abstractEmotionally pleasant experiences trigger repetition in humans whilst their emotional opposite lead to avoidance/refusal of activities. Human interest, a key factor in everyday human life, can be quite useful in the evaluation of participant engagement on activities and their optimization, so as to maximize interest and motivation. A glaring issue however comes from subtle demonstrators associated with human interest, which converge onto its complex assessment/quantization. Yet, there is an inherent correlation between human interest and its provoked emotional response which can be explored in tandem with emotion recognition for the development of an engagement metrics tool. Such a mechanism would be highly beneficial for the improvement of several activities involved with learning and security, by enabling precise control over participant enthusiasm. In this paper we present an interest mapping technique which provides the user with spatio-temporal information extracted from a participant crowd. The technique aims to extract emotional cues from participant facial data, assessing its spatial and temporal distributions over the course of scenarios such as therapy sessions and lectures. The goal is to demonstrate where and when activities must be improved in order to retain attention, maximize efficacy and assure emotional pleasantness in participants. For validation, this study makes use of data collected over a college lecture so as to provide readers with a real demonstration of the technique's advantages.pt
dc.language.isoengpt
dc.relationFCT 2020.05620.BDpt
dc.relationFCT UIDB/00048/2020.pt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt
dc.subjectemotion recognitionpt
dc.subjectmachine learningpt
dc.subjecthuman perceptionpt
dc.titleCrowd Interest Mapping to Assess Engagementpt
dc.typearticle-
degois.publication.firstPage167pt
degois.publication.lastPage180pt
degois.publication.issue02pt
degois.publication.titleInternational journal of online and biomedical engineeringpt
dc.peerreviewedyespt
dc.identifier.doi10.3991/ijoe.v18i02.25445pt
degois.publication.volume18pt
dc.date.embargo2022-01-01*
uc.date.periodoEmbargo0pt
item.grantfulltextopen-
item.fulltextCom Texto completo-
item.languageiso639-1en-
crisitem.author.orcid0000-0003-4015-4111-
crisitem.author.orcid0000-0002-0251-9047-
crisitem.author.orcid0000-0002-4903-3554-
Appears in Collections:FCTUC Eng.Electrotécnica - Artigos em Revistas Internacionais
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