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A k-NN classification based VR user verification using eye movement and ocular biomechanics

Version 2 2024-06-04, 02:21
Version 1 2020-01-21, 02:05
conference contribution
posted on 2024-06-04, 02:21 authored by J Iskander, A Abobakr, M Attia, K Saleh, D Nahavandi, M Hossny, S 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

Pagination

1844-1848

Location

Bari, Italy

Start date

2019-10-06

End date

2019-10-09

ISSN

1062-922X

ISBN-13

9781728145693

Language

eng

Publication classification

E1 Full written paper - refereed

Title of proceedings

SMC 2019 : Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics

Event

Systems, Man and Cybernetics. Conference (2019 : Bari, Italy)

Publisher

IEEE

Place of publication

Piscataway, N.J.