Publication
Comparing Bayesian Networks to Classify Facial Expressions
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | |
| datacite.subject.fos | Engenharia e Tecnologia::Engenharia Mecânica | |
| dc.contributor.author | Simplício, Carlos | |
| dc.contributor.author | Prado, José | |
| dc.contributor.author | Dias, Jorge | |
| dc.date.accessioned | 2025-10-28T13:15:10Z | |
| dc.date.available | 2025-10-28T13:15:10Z | |
| dc.date.issued | 2010 | |
| dc.description | Conference name - IASTED International Conference on Robotics and Applications, RA 2010; Conference date - 1 November 2010 - 3 November 2010; Conference code - 89095 | |
| dc.description | Fonte: https://www.researchgate.net/publication/235887197_Comparing_Bayesian_Networks_to_Classify_Facial_Expressions | |
| dc.description.abstract | In this paper are presented two distinct Bayesian networks to analyse human beings' facial expressions. Both classifiers are completely defined: structure of the networks, belief variables and respective events, likelihoods, initial priors and procedure to change dynamically priors. The performance (relatively to the convergence) of the two approaches is compared. For both networks, the classification is done associating the facial expression to the probabilities of five emotional states: anger, fear, happy, sad and neutral. A justification for the usage of this set is presented: it is based in emotional states presented by human beings during social relationships. Classifiers as these described here can be used in Human Robot Interation. We believe that this interaction shall be done in a similar way of that used by human beings to communicate between them and, after all, facial expressions is one of the main non-verbal means of communication used by human. | eng |
| dc.description.sponsorship | The authors gratefully acknowledge support from Institute of Systems and Robotics at Coimbra University (ISR-UC), Institute Polytechnic of Leiria (IPL) and from Portuguese Foundation for Science and Technology (FCT). | |
| dc.identifier.citation | Simplicio, C., Prado, J., & Dias, J. (2010). Comparing bayesian networks to classify facial expressions. In Proceedings of RA-IASTED, The 15th IASTED International Conference on Robotics and Applications, Cambridge, Massachusetts, USA. DOI: https://doi.org/10.2316/p.2010.706-065. | |
| dc.identifier.doi | 10.2316/p.2010.706-065 | |
| dc.identifier.isbn | 978-088986862-5 | |
| dc.identifier.issn | 1027264X | |
| dc.identifier.uri | http://hdl.handle.net/10400.8/14413 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Acta Press | |
| dc.relation.hasversion | https://www.actapress.com/PaperInfo.aspx?paperId=41547 | |
| dc.relation.ispartof | IASTED Technology Conferences / 705: ARP / 706: RA / 707: NANA / 728: CompBIO | |
| dc.rights.uri | N/A | |
| dc.subject | Facial Expressions | |
| dc.subject | Bayesian Networks | |
| dc.subject | HRI | |
| dc.title | Comparing Bayesian Networks to Classify Facial Expressions | eng |
| dc.type | conference paper | |
| dspace.entity.type | Publication | |
| oaire.citation.conferenceDate | 2010-11 | |
| oaire.citation.conferencePlace | Cambridge, Massachusetts, USA | |
| oaire.citation.title | Proceedings of the IASTED International Conference on Robotics and Applications | |
| oaire.version | http://purl.org/coar/version/c_ab4af688f83e57aa | |
| person.familyName | Simplício | |
| person.givenName | Carlos | |
| person.identifier.orcid | 0000-0001-6281-4059 | |
| relation.isAuthorOfPublication | 2e15bd33-f7a7-466f-8013-1fdd73b75e7c | |
| relation.isAuthorOfPublication.latestForDiscovery | 2e15bd33-f7a7-466f-8013-1fdd73b75e7c |
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- In this paper are presented two distinct Bayesian networks to analyse human beings' facial expressions. Both classifiers are completely defined: structure of the networks, belief variables and respective events, likelihoods, initial priors and procedure to change dynamically priors. The performance (relatively to the convergence) of the two approaches is compared. For both networks, the classification is done associating the facial expression to the probabilities of five emotional states: anger, fear, happy, sad and neutral. A justification for the usage of this set is presented: it is based in emotional states presented by human beings during social relationships. Classifiers as these described here can be used in Human Robot Interation. We believe that this interaction shall be done in a similar way of that used by human beings to communicate between them and, after all, facial expressions is one of the main non-verbal means of communication used by human.
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