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5 October 2023 Bias-mitigated face ID using secure generative transforms
Suhas Sreehari, Hector Santos-Villalobos
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Proceedings Volume 12675, Applications of Machine Learning 2023; 126750K (2023) https://doi.org/10.1117/12.2677755
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States
Abstract
In this paper, we create mix-and-matched generative networks to address privacy and bias concerns in face recognition systems. There has been a rise in bias based on religion, gender, and race. To preserve the robustness of face ID systems while masking these bias-inducing facial features, we map the faces to neutral natural landscape images. This still leaves the possibility of estimating facial features from the landscape images. We address this issue through decorrelation shuffling functions between the latent spaces of the encoder and the generator networks, as a way of decorrelating facial and landscape features and preventing hacking.
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Suhas Sreehari and Hector Santos-Villalobos "Bias-mitigated face ID using secure generative transforms", Proc. SPIE 12675, Applications of Machine Learning 2023, 126750K (5 October 2023); https://doi.org/10.1117/12.2677755
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KEYWORDS
Transform theory
Education and training
Image processing
Databases
Design and modelling
Image acquisition
Skin
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