Enhancing Resilience in Biometric Research: Generation of 3D Synthetic Face Data Using Advanced 3D Character Creation Techniques from High-Fidelity Video Games and Animation
- Biometric authentication plays a vital role in various everyday applications with increasing demands for reliability and security. However, the use of real biometric data for research raises privacy concerns and data scarcity issues. A promising approach using synthetic biometric data to address the resulting unbalanced representation and bias, as well as the limited availability of diverse datasets for the development and evaluation of biometric systems, has emerged. Methods for a parameterized generation of highly realistic synthetic data are emerging and the necessary quality metrics to prove that synthetic data can compare to real data are open research tasks. The generation of 3D synthetic face data using game engines’ capabilities of generating varied realistic virtual characters is explored as a possible alternative for generating synthetic face data while maintaining reproducibility and ground truth, as opposed to other creation methods. While synthetic data offer several benefits, including improved resilience against data privacy concerns, the limitations and challenges associated with their usage are addressed. Our work shows concurrent behavior in comparing semi-synthetic data as a digital representation of a real identity with their real datasets. Despite slight asymmetrical performance in comparison with a larger database of real samples, a promising performance in face data authentication is shown, which lays the foundation for further investigations with digital avatars and the creation and analysis of fully synthetic data. Future directions for improving synthetic biometric data generation and their impact on advancing biometrics research are discussed.
Document Type: | Article |
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Language: | English |
Author: | Florian Erwin Blümel, Mathias Schulz, Ralph Breithaupt, Norbert Jung, Robert Lange |
Parent Title (English): | Sensors |
Volume: | 24 |
Issue: | 9 |
Article Number: | 2750 |
Number of pages: | 11 |
ISSN: | 1424-8220 |
URN: | urn:nbn:de:hbz:1044-opus-82894 |
DOI: | https://doi.org/10.3390/s24092750 |
PMID: | https://pubmed.ncbi.nlm.nih.gov/38732856 |
Publisher: | MDPI |
Place of publication: | Basel |
Publishing Institution: | Hochschule Bonn-Rhein-Sieg |
Date of first publication: | 2024/04/25 |
Copyright: | © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. |
Funding: | As part of the BIOLAB project at the Biometric Evaluation Center, this work was supported by the Federal Office for Information Security (BSI, Project BIOLAB, project id 423, order number 105538/2021) and the Institute of Safety and Security Research (ISF) of the Hochschule Bonn-Rhein-Sieg. |
Keyword: | avatars; diversity; face biometrics; face data; realism; resilience; synthetic biometric data |
Departments, institutes and facilities: | Fachbereich Informatik |
Fachbereich Ingenieurwissenschaften und Kommunikation | |
Institut für Sicherheitsforschung (ISF) | |
Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE) | |
Projects: | Biometrie-Analyse-Labor (Biolab) |
Dewey Decimal Classification (DDC): | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 006 Spezielle Computerverfahren |
Open access funding: | Deutsche Forschungsgemeinschaft / DFG Förderung Open Access Publikationskosten 2023 - 2025 |
Entry in this database: | 2024/05/02 |
Licence (German): | Creative Commons - CC BY - Namensnennung 4.0 International |