Eye Typing using Markov and Active Appearance Models
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Appearance-based Eye Gaze Estimation
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Non-Intrusive Gaze Tracking Using Artificial Neural Networks
Non-Intrusive Gaze Tracking Using Artificial Neural Networks
Eye Gaze Tracking under Natural Head Movements
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sparse and Semi-supervised Visual Mapping with the S^3GP
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
2006 Special Issue: Modeling attention to salient proto-objects
Neural Networks
Rapid Prototyping of Activity Recognition Applications
IEEE Pervasive Computing
An Incremental Learning Method for Unconstrained Gaze Estimation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
In the Eye of the Beholder: A Survey of Models for Eyes and Gaze
IEEE Transactions on Pattern Analysis and Machine Intelligence
Toward Mobile Eye-Based Human-Computer Interaction
IEEE Pervasive Computing
Eye Movement Analysis for Activity Recognition Using Electrooculography
IEEE Transactions on Pattern Analysis and Machine Intelligence
New Methods in Iris Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Towards pervasive eye tracking using low-level image features
Proceedings of the Symposium on Eye Tracking Research and Applications
Eye gesture recognition on portable devices
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
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In mobile daily life settings, video-based gaze tracking faces challenges associated with changes in lighting conditions and artefacts in the video images caused by head and body movements. These challenges call for the development of new methods that are robust to such influences. In this paper we investigate the problem of gaze estimation, more specifically how to discriminate different gaze directions from eye images. In a 17 participant user study we record eye images for 13 different gaze directions from a standard webcam. We extract a total of 50 features from these images that encode information on color, intensity and orientations. Using mRMR feature selection and a k-nearest neighbor (kNN) classifier we show that we can estimate these gaze directions with a mean recognition performance of 86%.