TY  - JOUR
A1  - Rack, Christian
A1  - Fernando, Tamara
A1  - Yalcin, Murat
A1  - Hotho, Andreas
A1  - Latoschik, Marc Erich
T1  - Who is Alyx? A new behavioral biometric dataset for user identification in XR
JF  - Frontiers in Virtual Reality
N2  - Introduction: This paper addresses the need for reliable user identification in Extended Reality (XR), focusing on the scarcity of public datasets in this area.

Methods: We present a new dataset collected from 71 users who played the game “Half-Life: Alyx” on an HTC Vive Pro for 45 min across two separate sessions. The dataset includes motion and eye-tracking data, along with physiological data from a subset of 31 users. Benchmark performance is established using two state-of-the-art deep learning architectures, Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU).

Results: The best model achieved a mean accuracy of 95% for user identification within 2 min when trained on the first session and tested on the second.

Discussion: The dataset is freely available and serves as a resource for future research in XR user identification, thereby addressing a significant gap in the field. Its release aims to facilitate advancements in user identification methods and promote reproducibility in XR research.
KW  - dataset
KW  - behaviometric
KW  - deep learning
KW  - physiological dataset
KW  - user identification
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-353979
SN  - 2673-4192
VL  - 4
ER  -