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Measuring Hidden Bias within Face Recognition via Racial Phenotypes [other] Open Access
Recent work reports disparate performance for intersectional racial groups across face recognition tasks: face verification and identification. However, the definition of those racial groups has a significant impact on the underlying findings of such racial bias analysis. Previous studies define these groups based on either demographic information (e.g. African, Asian etc.) or skin tone (e.g. lighter or darker skins). The use of such sensitive or broad group definitions has disadvantages for bias investigation and subsequent counter-bias solutions design. By contrast, this study introduces an alternative racial bias analysis methodology via facial phenotype attributes for face recognition. We use the set of observable characteristics of an individual face where a race-related facial phenotype is hence specific to the human face and correlated to the racial profile of the subject. We propose categorical test cases to investigate the individual influence of those attributes on bias within face recognition tasks. We compare our phenotype-based grouping methodology with previous grouping strategies and show that phenotype-based groupings uncover hidden bias without reliance upon any potentially protected attributes or ill-defined grouping strategies. Furthermore, we contribute corresponding phenotype attribute category labels for two face recognition tasks: RFW for face verification and VGGFace2 (test set) for face identification.
Descriptions
- Resource type
- Other
- Contributors
- Creator:
Yucer, Seyma
1
Contact person: Yucer, Seyma 1
Editor: Breckon, Toby 1
Tektas, Furkan 2
Al Moubayed, Noura 1
1 Durham University, UK
2 BuboAI, Middlesbrough, UK
- Funder
- Research methods
- Other description
-
Deposit consists of metadata files of two datasets and one machine learning model trained parameters. Code published on GitHub: https://github.com/seymayucer/FacialPhenotypes
Originally published as: Understanding racial bias using facial phenotypes
- Keyword
- Facial phenotypes
Labels
Pre-trained models
- Subject
-
Face perception--Racial bias
- Location
-
Durham, England, United Kingdom
- Language
- English
- Cited in
- arxiv:2110.09839
- Identifier
- ark:/32150/r2hm50tr746
doi:10.15128/r2hm50tr746
- Rights
- Creative Commons Attribution 4.0 International (CC BY)
- Publisher
-
Durham University
- Date Created
File Details
- Depositor
- S. Yucer Tektas
- Date Uploaded
- 20 April 2021, 12:04:16
- Date Modified
- 5 January 2022, 11:01:47
- Audit Status
- Audits have not yet been run on this file.
- Characterization
-
File format: zip (ZIP Format)
Mime type: application/zip
File size: 242817654
Last modified: 2021:04:20 13:52:28+01:00
Filename: model_and_labels.zip
Original checksum: 2774ea5e7a10aab0b9db9eb6cdab8450
| User Activity | Date |
|---|---|
| User N. Syrotiuk has updated Measuring Hidden Bias within Face Recognition via Racial Phenotypes [other] | about 3 years ago |
| User N. Syrotiuk has updated Measuring Hidden Bias within Face Recognition via Racial Phenotypes [other] | about 3 years ago |
| User S. Yucer Tektas has updated UNDERSTANDING RACIAL BIAS USING FACIAL PHENOTYPES | almost 4 years ago |
| User S. Yucer Tektas has updated UNDERSTANDING RACIAL BIAS USING FACIAL PHENOTYPES | almost 4 years ago |
| User S. Yucer Tektas has deposited model_and_labels.zip | almost 4 years ago |