Context-adaptive and user-centric facial emotion classification

Doulamis, N

dc.contributor.author	Doulamis, N	en
dc.date.accessioned	2014-03-01T02:43:11Z
dc.date.available	2014-03-01T02:43:11Z
dc.date.issued	2005	en
dc.identifier.issn	15224880	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31283
dc.subject	Adaptive Architecture	en
dc.subject	Functional Analysis	en
dc.subject	Low Complexity	en
dc.subject	Process Capability	en
dc.subject.other	Adaptable architecture	en
dc.subject.other	Context environment	en
dc.subject.other	Facial emotions	en
dc.subject.other	Processing capabilities	en
dc.subject.other	Adaptive algorithms	en
dc.subject.other	Data storage equipment	en
dc.subject.other	Database systems	en
dc.subject.other	Image processing	en
dc.subject.other	Program processors	en
dc.subject.other	Real time systems	en
dc.subject.other	Face recognition	en
dc.title	Context-adaptive and user-centric facial emotion classification	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICIP.2005.1529989	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICIP.2005.1529989	en
heal.identifier.secondary	1529989	en
heal.publicationDate	2005	en
heal.abstract	In this paper, we proposed a context-adaptive and user-centric emotion classification scheme of low complexity. Different people express their feelings In a different way under different circumstances (different context). Therefore, an adaptable architecture is proposed in this paper able to automatically update its performance to a particular individual (user-centric) and context environment (context-adaptive). As a result, the same expressions may lead to different emotional states in accordance to the specific environment to these feelings are expressed. The adaptation is performed using concepts derived from functional analysis. The presented adaptable architecture requires low memory and processing capabilities and thus it can be embedded in smart pervasive devices of low processing requirements. Experimental results on real-life databases illustrate the efficiency of the proposed scheme in recognizing the emotion of different people or even the same under different circumstances. © 2005 IEEE.	en
heal.journalName	Proceedings - International Conference on Image Processing, ICIP	en
dc.identifier.doi	10.1109/ICIP.2005.1529989	en
dc.identifier.volume	2	en
dc.identifier.spage	53	en
dc.identifier.epage	56	en