Combination of multiple extraction algorithms in the detection of facial features

Ioannou, S; Wallace, M; Karpouzis, K; Raouzaiou, A; Kollias, S

dc.contributor.author	Ioannou, S	en
dc.contributor.author	Wallace, M	en
dc.contributor.author	Karpouzis, K	en
dc.contributor.author	Raouzaiou, A	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T02:43:10Z
dc.date.available	2014-03-01T02:43:10Z
dc.date.issued	2005	en
dc.identifier.issn	15224880	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31268
dc.subject	Automatic Detection	en
dc.subject	Boundary Detection	en
dc.subject	Error Resilience	en
dc.subject	Expression Analysis	en
dc.subject	Facial Features	en
dc.subject	Feature Extraction	en
dc.subject	Human Computer Interaction	en
dc.subject	Multiple Channels	en
dc.subject	Rule Based	en
dc.subject.other	Automatic detection	en
dc.subject.other	Boundary detection	en
dc.subject.other	Facial features	en
dc.subject.other	Rule based expression	en
dc.subject.other	Algorithms	en
dc.subject.other	Feature extraction	en
dc.subject.other	Human computer interaction	en
dc.subject.other	Image analysis	en
dc.subject.other	Image processing	en
dc.subject.other	Face recognition	en
dc.title	Combination of multiple extraction algorithms in the detection of facial features	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICIP.2005.1530071	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICIP.2005.1530071	en
heal.identifier.secondary	1530071	en
heal.publicationDate	2005	en
heal.abstract	Automated analysis of facial images for the estimation of the displayed expression is essential in the design of intuitive and accessible human computer interaction systems. In existing rule-based expression recognition approaches, different feature extraction techniques have been tested that allow for the automatic detection of feature points, providing the required input for a rule based expression analysis; each one of these techniques outperforms others under specific constraints. In this paper we propose a feature extraction system which combines analysis from multiple channels based on their confidence, to result in better, error resilient facial feature boundary detection. The proposed approach has been implemented as an extension to an existing expression analysis system in the framework of the IST ERMIS project. © 2005 IEEE.	en
heal.journalName	Proceedings - International Conference on Image Processing, ICIP	en
dc.identifier.doi	10.1109/ICIP.2005.1530071	en
dc.identifier.volume	2	en
dc.identifier.spage	378	en
dc.identifier.epage	381	en