Conference Publication Details
Mandatory Fields
Lemley, J,Kar, A,Corcoran, P,
Eye Tracking in Augmented Spaces: a Deep Learning Approach
2018 IEEE GAMES, ENTERTAINMENT, MEDIA CONFERENCE (GEM)
2018
January
Published
1
()
Optional Fields
Augmented reality Virtual reality gaze estimation deep learning convolutional neural networks smart spaces GAZE TRACKING
396
401
The use of deep learning for estimating eye gaze in augmented spaces is investigated in this work. There are two primary ways of interacting with augmented spaces. The first involves the use of AR/VR systems; the second involves devices that respond to the user's gaze directly. This domain can overlap with AR/VR environments but is not exclusive to them and contains its own unique set of issues. Deep learning methods for eye tracking that are capable of performing with minimal power consumption are investigated for both problems.
Grant Details
Publication Themes