Who is Alyx? A new behavioral biometric dataset for user identification in XR
Please always quote using this URN: urn:nbn:de:bvb:20-opus-353979
- 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 NetworksIntroduction: 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.…
Author: | Christian Rack, Tamara Fernando, Murat Yalcin, Andreas Hotho, Marc Erich Latoschik |
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URN: | urn:nbn:de:bvb:20-opus-353979 |
Document Type: | Journal article |
Faculties: | Fakultät für Mathematik und Informatik / Institut für Informatik |
Language: | English |
Parent Title (English): | Frontiers in Virtual Reality |
ISSN: | 2673-4192 |
Year of Completion: | 2023 |
Volume: | 4 |
Article Number: | 1272234 |
Source: | Frontiers in Virtual Reality (2023) 4:1272234. https://doi.org/10.3389/frvir.2023.1272234 |
DOI: | https://doi.org/10.3389/frvir.2023.1272234 |
Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 005 Computerprogrammierung, Programme, Daten |
Tag: | behaviometric; dataset; deep learning; physiological dataset; user identification |
Release Date: | 2024/05/08 |
Date of first Publication: | 2023/11/10 |
Licence (German): | CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International |