Emotion recognition through facial expression analysis based on a neurofuzzy network

Ioannou, SV; Raouzaiou, AT; Tzouvaras, VA; Mailis, TP; Karpouzis, KC; Kollias, SD

dc.contributor.author	Ioannou, SV	en
dc.contributor.author	Raouzaiou, AT	en
dc.contributor.author	Tzouvaras, VA	en
dc.contributor.author	Mailis, TP	en
dc.contributor.author	Karpouzis, KC	en
dc.contributor.author	Kollias, SD	en
dc.date.accessioned	2014-03-01T01:22:17Z
dc.date.available	2014-03-01T01:22:17Z
dc.date.issued	2005	en
dc.identifier.issn	0893-6080	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16514
dc.subject	Activation evaluation emotion representation	en
dc.subject	Adaptation	en
dc.subject	Facial expression analysis	en
dc.subject	MPEG-4 facial animation parameters	en
dc.subject	Neurofuzzy network	en
dc.subject	Rule extraction	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.other	Communication systems	en
dc.subject.other	Data reduction	en
dc.subject.other	Image analysis	en
dc.subject.other	Neural networks	en
dc.subject.other	Robustness (control systems)	en
dc.subject.other	Facial animation parameters (FAP)	en
dc.subject.other	Facial expressions	en
dc.subject.other	Man machine communication systems	en
dc.subject.other	Neurofuzzy systems	en
dc.subject.other	Face recognition	en
dc.subject.other	accuracy	en
dc.subject.other	article	en
dc.subject.other	artificial neural network	en
dc.subject.other	emotion	en
dc.subject.other	facial expression	en
dc.subject.other	human computer interaction	en
dc.subject.other	learning	en
dc.subject.other	model	en
dc.subject.other	priority journal	en
dc.subject.other	recognition	en
dc.subject.other	statistical analysis	en
dc.subject.other	technology	en
dc.subject.other	validation process	en
dc.subject.other	Adaptation, Psychological	en
dc.subject.other	Databases	en
dc.subject.other	Emotions	en
dc.subject.other	Facial Expression	en
dc.subject.other	Humans	en
dc.subject.other	Learning	en
dc.subject.other	Man-Machine Systems	en
dc.subject.other	Neural Networks (Computer)	en
dc.subject.other	Recognition (Psychology)	en
dc.subject.other	Visual Perception	en
dc.title	Emotion recognition through facial expression analysis based on a neurofuzzy network	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.neunet.2005.03.004	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.neunet.2005.03.004	en
heal.language	English	en
heal.publicationDate	2005	en
heal.abstract	Extracting and validating emotional cues through analysis of users' facial expressions is of high importance for improving the level of interaction in man machine communication systems. Extraction of appropriate facial features and consequent recognition of the user's emotional state that can be robust to facial expression variations among different users is the topic of this paper. Facial animation parameters (FAPs) defined according to the ISO MPEG-4 standard are extracted by a robust facial analysis system, accompanied by appropriate confidence measures of the estimation accuracy. A novel neurofuzzy system is then created, based on rules that have been defined through analysis of FAP variations both at the discrete emotional space, as well as in the 21) continuous activation-evaluation one. The neurofuzzy system allows for further learning and adaptation to specific users' facial expression characteristics, measured though FAP estimation in real life application of the system, using analysis by clustering of the obtained FAP values. Experimental studies with emotionally expressive datasets, generated in the EC IST ERMIS project indicate the good performance and potential of the developed technologies. (c) 2005 Elsevier Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	Neural Networks	en
dc.identifier.doi	10.1016/j.neunet.2005.03.004	en
dc.identifier.isi	ISI:000230710900007	en
dc.identifier.volume	18	en
dc.identifier.issue	4	en
dc.identifier.spage	423	en
dc.identifier.epage	435	en