A non-intrusive method for user focus of attention estimation in front of a computer monitor

Asteriadis, S; Tzouveli, P; Karpouzis, K; Kollias, S

dc.contributor.author	Asteriadis, S	en
dc.contributor.author	Tzouveli, P	en
dc.contributor.author	Karpouzis, K	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T02:45:03Z
dc.date.available	2014-03-01T02:45:03Z
dc.date.issued	2008	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32116
dc.subject	Eye Gaze	en
dc.subject	Eye Movement	en
dc.subject	Focus of Attention	en
dc.subject	Infrared	en
dc.subject	Machine Learning	en
dc.subject	Real Time	en
dc.subject.other	Computer screens	en
dc.subject.other	Detection and tracking	en
dc.subject.other	Eye-gaze	en
dc.subject.other	Focus of Attention	en
dc.subject.other	Head pose	en
dc.subject.other	Head position	en
dc.subject.other	Infra-red cameras	en
dc.subject.other	Machine-learning	en
dc.subject.other	Non-intrusive method	en
dc.subject.other	Real-time feedback	en
dc.subject.other	Special hardware	en
dc.subject.other	Wearable devices	en
dc.subject.other	Web camera	en
dc.subject.other	Cameras	en
dc.subject.other	Computer monitors	en
dc.subject.other	Eye movements	en
dc.subject.other	Face recognition	en
dc.subject.other	Tracking (position)	en
dc.subject.other	Gesture recognition	en
dc.title	A non-intrusive method for user focus of attention estimation in front of a computer monitor	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/AFGR.2008.4813330	en
heal.identifier.secondary	http://dx.doi.org/10.1109/AFGR.2008.4813330	en
heal.identifier.secondary	4813330	en
heal.publicationDate	2008	en
heal.abstract	In this work, we present a system that estimates a user's focus of attention in front of a computer screen, using a web camera, based on detection and tracking of the user's head position and eye movements. Utilizing machine learning concepts, the system gives real time feedback on the user's attention, by combining information coming from eye gaze, head pose, and distance from the screen. The system is completely un-intrusive and no special hardware (such as infrared cameras or wearable devices) is needed. Furthermore, it adjusts to every user, not necessitating initial calibration, and can work under real and unconstrained conditions in terms of lighting. © 2008 IEEE.	en
heal.journalName	2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008	en
dc.identifier.doi	10.1109/AFGR.2008.4813330	en