Authors:
Adam Strupczewski
1
;
Błażej Czupryński
1
;
Jacek Naruniec
2
and
Kamil Mucha
1
Affiliations:
1
Samsung Electronics Poland, Poland
;
2
Warsaw University of Technology, Poland
Keyword(s):
Eye Gaze Tracking, Head Pose Tracking, Iris Localization, Feature Matching, Pose Estimation.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Enterprise Information Systems
;
Human and Computer Interaction
;
Human-Computer Interaction
;
Motion, Tracking and Stereo Vision
;
Optical Flow and Motion Analyses
Abstract:
This paper presents a novel eye gaze estimation method based on calculating the gaze vector in a geometric
approach. There have been many publications in the topic of eye gaze estimation, but most are related to
using dedicated infra red equipment and corneal glints. The presented approach, on the other hand, assumes
that only an RGB input image of the user’s face is available. Furthermore, it requires no calibration but only
simple one-frame initialization. In comparison to other systems presented in literature, our method has better
accuracy. The presented method relies on determining the 3D location of the face and eyes in the initialization
frame, tracking these locations in each consecutive frame and using this knowledge to estimating the gaze
vector and point where the user is looking. The algorithm runs in real time on mobile devices.