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Emotionally expressive motion controller for virtual character locomotion animations

2022Journal article Restricted access
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dc.contributor.authorSilva, Diogo
dc.contributor.authorSantos, Pedro A.
dc.contributor.authorDias, Joao
dc.date.accessioned2023-05-11T12:42:18Z
dc.date.available2023-05-11T12:42:18Z
dc.date.issued2022
dc.description.abstractStyle and emotional expressiveness are essential aspects of virtual character computer animation. For a virtual character to display different emotions, motion capture data conveying each desired style has to be recorded, even if the baseline motion is the same. Animators then have to refine and conjoin each recording in order to create the final animations making it a timely and costly process. Although there have been efforts made into the automatic generation of motions, the problem persists that, for each new desired emotion, reference data displaying said emotion has to be readily available and a new motion has to be learned from scratch. By combining Machine Learning with Emotion Analysis - in particular Laban Movement Analysis and the Pleasure, Arousal, Dominance Emotional State Model - we have developed a system that is capable of not only identifying the perceived emotion of locomotion animations but that also allows users to alter the character's expressed emotion in real time and without the need of additional data.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/ISM55400.2022.00049pt_PT
dc.identifier.isbn978-1-6654-7172-5
dc.identifier.urihttp://hdl.handle.net/10400.1/19556
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIEEEpt_PT
dc.relationInstituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectComputer animationpt_PT
dc.subjectmachine learningpt_PT
dc.subjectSentiment analysispt_PT
dc.subjectMotion synthesispt_PT
dc.titleEmotionally expressive motion controller for virtual character locomotion animationspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleInstituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50021%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FCCI-COM%2F30787%2F2017/PT
oaire.citation.endPage219pt_PT
oaire.citation.startPage218pt_PT
oaire.citation.title2022 IEEE International Symposium on Multimedia (ISM)pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream3599-PPCDT
person.familyNameDias
person.givenNameJoao
person.identifier.orcid0000-0002-6271-6501
person.identifier.scopus-author-id7201934507
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication.latestForDiscoveryad92aacb-15e6-4f18-9d1f-e12f8e14c985
relation.isProjectOfPublication0b14d63a-8f78-4e31-8a86-b72e1f07871f
relation.isProjectOfPublication9237bac8-45b7-49c6-9799-a1a7e3794f65
relation.isProjectOfPublication.latestForDiscovery9237bac8-45b7-49c6-9799-a1a7e3794f65

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