Conference Publication Details
Mandatory Fields
Varkarakis, V;Bazrafkan, S;Corcoran, P
2018 IEEE GAMES, ENTERTAINMENT, MEDIA CONFERENCE (GEM)
A Deep Learning approach to Segmentation of Distorted Iris regions in Head-Mounted Displays
2018
January
Published
1
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Optional Fields
GOOGLE-GLASS AUGMENTED REALITY AUTHENTICATION DEVICES WORLD
402
406
In this paper, we consider the next generation of wearable AR/VR display glasses and the challenges of personal authentication on such devices. The use of iris authentication as a mean of creating a seamless biometric link between the user and his personal data offers a viable approach, but due to the likely location of user-facing cameras there are some challenges in achieving an accurate segmentation of the iris. In this paper, a deep neural network was trained to accurately segment distorted iris regions. An appropriate augmentation method is presented to generate the distorted iris dataset used for training from publicly available frontal iris datasets. The proposed method shows promising results in segmenting off-axis iris images in unconstrained conditions.
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