HEAL DSpace

Feature extraction and selection for inferring user engagement in an hci environment

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dc.contributor.author Asteriadis, S en
dc.contributor.author Karpouzis, K en
dc.contributor.author Kollias, S en
dc.date.accessioned 2014-03-01T02:46:10Z
dc.date.available 2014-03-01T02:46:10Z
dc.date.issued 2009 en
dc.identifier.issn 03029743 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/32576
dc.subject Eye Gaze en
dc.subject Facial Feature tracking en
dc.subject Head Pose en
dc.subject User engagement en
dc.subject.other Eye Gaze en
dc.subject.other Facial Feature tracking en
dc.subject.other Feature extraction and selection en
dc.subject.other Head Pose en
dc.subject.other Lighting conditions en
dc.subject.other User engagement en
dc.subject.other Computer hardware en
dc.subject.other Computer monitors en
dc.subject.other E-learning en
dc.subject.other Electric currents en
dc.subject.other Feature extraction en
dc.subject.other Internet en
dc.subject.other Knowledge management en
dc.subject.other Multimedia systems en
dc.subject.other Human computer interaction en
dc.title Feature extraction and selection for inferring user engagement in an hci environment en
heal.type conferenceItem en
heal.identifier.primary 10.1007/978-3-642-02574-7_3 en
heal.identifier.secondary http://dx.doi.org/10.1007/978-3-642-02574-7_3 en
heal.publicationDate 2009 en
heal.abstract In this paper, we present our work towards estimating the engagement of a person to the displayed information of a computer monitor. Deciding whether a user is attentive or not, and frustrated or not, helps adapting the displayed information of a computer in special environments, such as e-learning. The aim of the current work is the development of a method that can work user-independently, without necessitating special lighting conditions and with only requirements in terms of hardware, a computer and a web-camera. © 2009 Springer Berlin Heidelberg. en
heal.journalName Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) en
dc.identifier.doi 10.1007/978-3-642-02574-7_3 en
dc.identifier.volume 5610 LNCS en
dc.identifier.issue PART 1 en
dc.identifier.spage 22 en
dc.identifier.epage 29 en


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