Multimodal emotion recognition from expressive faces, body gestures and speech

Caridakis, G; Castellano, G; Kessous, L; Raouzaiou, A; Malatesta, L; Asteriadis, S; Karpouzis, K

dc.contributor.author	Caridakis, G	en
dc.contributor.author	Castellano, G	en
dc.contributor.author	Kessous, L	en
dc.contributor.author	Raouzaiou, A	en
dc.contributor.author	Malatesta, L	en
dc.contributor.author	Asteriadis, S	en
dc.contributor.author	Karpouzis, K	en
dc.date.accessioned	2014-03-01T02:44:51Z
dc.date.available	2014-03-01T02:44:51Z
dc.date.issued	2007	en
dc.identifier.issn	15715736	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31974
dc.subject	Affective body language	en
dc.subject	Affective speech	en
dc.subject	Emotion recognition	en
dc.subject	Multimodal fusion	en
dc.title	Multimodal emotion recognition from expressive faces, body gestures and speech	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-0-387-74161-1_41	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-0-387-74161-1_41	en
heal.publicationDate	2007	en
heal.abstract	In this paper we present a multimodal approach for the recognition of eight emotions that integrates information from facial expressions, body movement and gestures and speech. We trained and tested a model with a Bayesian classifier, using a multimodal corpus with eight emotions and ten subjects. First individual classifiers were trained for each modality. Then data were fused at the feature level and the decision level. Fusing multimodal data increased very much the recognition rates in comparison with the unimodal systems: the multimodal approach gave an improvement of more than 10% with respect to the most successful unimodal system. Further, the fusion performed at the feature level showed better results than the one performed at the decision level. © 2007 International Federation for Information Processing.	en
heal.journalName	IFIP International Federation for Information Processing	en
dc.identifier.doi	10.1007/978-0-387-74161-1_41	en
dc.identifier.volume	247	en
dc.identifier.spage	375	en
dc.identifier.epage	388	en