User modeling via gesture and head pose expressivity features

Caridakis, G; Asteriadis, S; Karpouzis, K

dc.contributor.author	Caridakis, G	en
dc.contributor.author	Asteriadis, S	en
dc.contributor.author	Karpouzis, K	en
dc.date.accessioned	2014-03-01T02:47:08Z
dc.date.available	2014-03-01T02:47:08Z
dc.date.issued	2010	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/33012
dc.subject	Context Aware	en
dc.subject	Emotion Recognition	en
dc.subject	Facial Expression	en
dc.subject	Multimedia Application	en
dc.subject	System Dynamics	en
dc.subject	User Model	en
dc.subject.other	Acoustic features	en
dc.subject.other	Analysis system	en
dc.subject.other	Computational formulations	en
dc.subject.other	Context-Aware	en
dc.subject.other	Dynamic Profiling	en
dc.subject.other	Emotion recognition	en
dc.subject.other	Facial Expressions	en
dc.subject.other	Head motion	en
dc.subject.other	Head pose	en
dc.subject.other	Multi-modal	en
dc.subject.other	Multimedia applications	en
dc.subject.other	Personalized interface	en
dc.subject.other	Physiological measurement	en
dc.subject.other	Statistical processing	en
dc.subject.other	User Modeling	en
dc.subject.other	Work Focus	en
dc.subject.other	Mathematical models	en
dc.subject.other	Pattern recognition systems	en
dc.subject.other	Semantics	en
dc.subject.other	Feature extraction	en
dc.title	User modeling via gesture and head pose expressivity features	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/SMAP.2010.5706868	en
heal.identifier.secondary	http://dx.doi.org/10.1109/SMAP.2010.5706868	en
heal.identifier.secondary	5706868	en
heal.publicationDate	2010	en
heal.abstract	Current work focuses on user modeling in terms of affective analysis that could in turn be used in intelligent personalized interfaces and systems, dynamic profiling and context-aware multimedia applications. The analysis performed within this work comprises of statistical processing and classification of automatically extracted gestural and head pose expressivity features. Computational formulation of qualitative expressive cues of body and head motion is performed and the resulting features are processed statistically, their correlation is studied and finally an emotion recognition attempt is presented based on these features. Significant emotion specific patterns and expressivity features interrelations are derived while the emotion recognition results indicate that the gestural and head pose expressivity features could supplement and enhance a multimodal affective analysis system incorporating an additional modality to be fused with other commonly used modalities such as facial expressions, prosodic and lexical acoustic features and physiological measurements. © 2010 IEEE.	en
heal.journalName	Proceedings - 2010 5th International Workshop on Semantic Media Adaptation and Personalization, SMAP 2010	en
dc.identifier.doi	10.1109/SMAP.2010.5706868	en
dc.identifier.spage	19	en
dc.identifier.epage	24	en