Longitudinal Study of Facial Biometrics at the BEZ: Temporal Variance Analysis
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arXiv
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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866916844464504832 |
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| author | Schulz, Mathias Spenke, Alexander Funk, Pia Blümel, Florian Rohde, Markus Breithaupt, Ralph Nolden, Gerd Jung, Norbert Lange, Robert |
| author_facet | Schulz, Mathias Spenke, Alexander Funk, Pia Blümel, Florian Rohde, Markus Breithaupt, Ralph Nolden, Gerd Jung, Norbert Lange, Robert |
| contents | This study presents findings from long-term biometric evaluations conducted at the Biometric Evaluation Center (bez). Over the course of two and a half years, our ongoing research with over 400 participants representing diverse ethnicities, genders, and age groups were regularly assessed using a variety of biometric tools and techniques at the controlled testing facilities. Our findings are based on the General Data Protection Regulation-compliant local bez database with more than 238.000 biometric data sets categorized into multiple biometric modalities such as face and finger. We used state-of-the-art face recognition algorithms to analyze long-term comparison scores. Our results show that these scores fluctuate more significantly between individual days than over the entire measurement period. These findings highlight the importance of testing biometric characteristics of the same individuals over a longer period of time in a controlled measurement environment and lays the groundwork for future advancements in biometric data analysis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_06858 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Longitudinal Study of Facial Biometrics at the BEZ: Temporal Variance Analysis Schulz, Mathias Spenke, Alexander Funk, Pia Blümel, Florian Rohde, Markus Breithaupt, Ralph Nolden, Gerd Jung, Norbert Lange, Robert Computer Vision and Pattern Recognition This study presents findings from long-term biometric evaluations conducted at the Biometric Evaluation Center (bez). Over the course of two and a half years, our ongoing research with over 400 participants representing diverse ethnicities, genders, and age groups were regularly assessed using a variety of biometric tools and techniques at the controlled testing facilities. Our findings are based on the General Data Protection Regulation-compliant local bez database with more than 238.000 biometric data sets categorized into multiple biometric modalities such as face and finger. We used state-of-the-art face recognition algorithms to analyze long-term comparison scores. Our results show that these scores fluctuate more significantly between individual days than over the entire measurement period. These findings highlight the importance of testing biometric characteristics of the same individuals over a longer period of time in a controlled measurement environment and lays the groundwork for future advancements in biometric data analysis. |
| title | Longitudinal Study of Facial Biometrics at the BEZ: Temporal Variance Analysis |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2507.06858 |