High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-View Head Pose Estimation using Neural Networks
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
A single camera eye-gaze tracking system with free head motion
Proceedings of the 2006 symposium on Eye tracking research & applications
Pose Estimation Based on Two Images from Different Views
WACV '07 Proceedings of the Eighth IEEE Workshop on Applications of Computer Vision
A single-camera remote eye tracker
PIT'06 Proceedings of the 2006 international tutorial and research conference on Perception and Interactive Technologies
Journal of Intelligent Manufacturing
Proceedings of the 9th conference on Computing Frontiers
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User attention recognition in front of a monitor or a specific task is a crucial issue in many applications, ranging from e-learning to driving. Visual input is very important when extracting information regarding a user's attention when recorded with a camera. However, intrusive equipment (special helmets, glasses equipped with cameras recording the eye movements, etc.) impose constraints on users spontaneity, especially when the target group consists of under aged users. In this paper, we propose a system for inferring user attention (state) in front of a computer monitor, only with the usage of a simple camera. The system can be used for real time applications and does not need calibration in terms of camera parameters. It can function under normal lighting conditions and needs no adaptation for each user.