Publication
A Face Attention Technique for a Robot Able to Interpret Facial Expressions
| datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | |
| datacite.subject.sdg | 03:Saúde de Qualidade | |
| datacite.subject.sdg | 07:Energias Renováveis e Acessíveis | |
| datacite.subject.sdg | 11:Cidades e Comunidades Sustentáveis | |
| dc.contributor.author | Simplício, Carlos | |
| dc.contributor.author | Prado, José | |
| dc.contributor.author | Dias, Jorge | |
| dc.date.accessioned | 2025-11-18T12:48:50Z | |
| dc.date.available | 2025-11-18T12:48:50Z | |
| dc.date.issued | 2010 | |
| dc.description | EISBN - 9783642116285 | |
| dc.description.abstract | Automatic facial expressions recognition using vision is an important subject towards human-robot interaction. Here is proposed a human face focus of attention technique and a facial expressions classifier (a Dynamic Bayesian Network) to incorporate in an autonomous mobile agent whose hardware is composed by a robotic platform and a robotic head. The focus of attention technique is based on the symmetry presented by human faces. By using the output of this module the autonomous agent keeps always targeting the human face frontally. In order to accomplish this, the robot platform performs an arc centered at the human; thus the robotic head, when necessary, moves synchronized. In the proposed probabilistic classifier the information is propagated, from the previous instant, in a lower level of the network, to the current instant. Moreover, to recognize facial expressions are used not only positive evidences but also negative. | eng |
| dc.description.sponsorship | The authors gratefully acknowledge support from EC-contract number BACS FP6-IST-027140, the contribution of the Institute of Systems and Robotics at Coimbra University and reviewers' comments. | |
| dc.identifier.citation | Simplício, C., Prado, J., Dias, J. (2010). A Face Attention Technique for a Robot Able to Interpret Facial Expressions. In: Camarinha-Matos, L.M., Pereira, P., Ribeiro, L. (eds) Emerging Trends in Technological Innovation. DoCEIS 2010. IFIP Advances in Information and Communication Technology, vol 314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11628-5_36. | |
| dc.identifier.doi | 10.1007/978-3-642-11628-5_36 | |
| dc.identifier.eissn | 1868-422X | |
| dc.identifier.isbn | 9783642116278 | |
| dc.identifier.isbn | 9783642116285 | |
| dc.identifier.issn | 1868-4238 | |
| dc.identifier.uri | http://hdl.handle.net/10400.8/14651 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Springer Nature | |
| dc.relation.hasversion | https://link.springer.com/chapter/10.1007/978-3-642-11628-5_36 | |
| dc.relation.ispartof | IFIP Advances in Information and Communication Technology | |
| dc.relation.ispartof | Emerging Trends in Technological Innovation | |
| dc.rights.uri | N/A | |
| dc.subject | Facial Symmetry | |
| dc.subject | Focus of Attention | |
| dc.subject | Dynamic Bayesian Network | |
| dc.title | A Face Attention Technique for a Robot Able to Interpret Facial Expressions | eng |
| dc.type | book part | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 342 | |
| oaire.citation.startPage | 335 | |
| oaire.citation.title | IFIP Advances in Information and Communication Technology | |
| oaire.citation.volume | 314 | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| 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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- Automatic facial expressions recognition using vision is an important subject towards human-robot interaction. Here is proposed a human face focus of attention technique and a facial expressions classifier (a Dynamic Bayesian Network) to incorporate in an autonomous mobile agent whose hardware is composed by a robotic platform and a robotic head. The focus of attention technique is based on the symmetry presented by human faces. By using the output of this module the autonomous agent keeps always targeting the human face frontally. In order to accomplish this, the robot platform performs an arc centered at the human; thus the robotic head, when necessary, moves synchronized. In the proposed probabilistic classifier the information is propagated, from the previous instant, in a lower level of the network, to the current instant. Moreover, to recognize facial expressions are used not only positive evidences but also negative.
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