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5 October 2023 Measuring transform invertibility with computational metrics
Awroni Bhaduri, Hector Santos-Villalobos, Suhas Sreehari
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Proceedings Volume 12675, Applications of Machine Learning 2023; 126750F (2023) https://doi.org/10.1117/12.2677717
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States
Abstract
Modern face ID systems are often plagued with loss of privacy. To address this, some face ID systems incorporate image transformations in the detection pipeline. In particular, we consider transforms that convert human face images to non-face images (such as landscape images) to mask sensitive and bias-prone facial features and preserve privacy, while maintaining identifiability. We propose two metrics that study the effectiveness of face image transformations used in privacy-preserving face ID systems. These metrics measure the invertibility of the transformations to ensure the meta-data of the face (e.g. race, sex, age, etc.) cannot be inferred from the transformed image.
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Awroni Bhaduri, Hector Santos-Villalobos, and Suhas Sreehari "Measuring transform invertibility with computational metrics", Proc. SPIE 12675, Applications of Machine Learning 2023, 126750F (5 October 2023); https://doi.org/10.1117/12.2677717
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KEYWORDS
Face image reconstruction
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