A k-NN classification based VR user verification using eye movement and ocular biomechanics
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conference contribution
posted on 2019-01-01, 00:00 authored by J Iskander, Ahmed Abobakr, M Attia, K Saleh, Darius Nahavandi, Mohammed Hossny, Saeid Nahavandi© 2019 IEEE. VR user identification is of utmost importance especially with the increased applications of VR that will include e-payment among other applications that requires a high level of security. Biometric identification through eye movement, has been used previously due to the intrinsic characteristics of eye movement that characterises a person uniquely. In this paper, we propose using eye movement along with extraocular muscle activations in VR user verification. The muscle activations are calculated using an ocular biomechanical model. The k-NN classification results showed approximately 90% accuracy when using a feature set with eye movement parameters (3 joint angles), muscle activations for all 6 muscles along with the VR object position in 3D. The classifier is a biometric VR user verification tool that provides an easy and non-intrusive methods that can be easily integrated in different VR applications that require user verification.
History
Event
Systems, Man and Cybernetics. Conference (2019 : Bari, Italy)Pagination
1844 - 1848Publisher
IEEELocation
Bari, ItalyPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2019-10-06End date
2019-10-09ISSN
1062-922XISBN-13
9781728145693Language
engPublication classification
E1 Full written paper - refereedTitle of proceedings
SMC 2019 : Proceedings of the 2019 IEEE International Conference on Systems, Man and CyberneticsUsage metrics
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