Facial Expressions as a Vulnerability in Face Recognition

• URL: http://arxiv.org/abs/2011.08809v2
• Date: Fri, 18 Jun 2021 08:27:24 GMT
• Title: Facial Expressions as a Vulnerability in Face Recognition
• Authors: Alejandro Pe\~na and Ignacio Serna and Aythami Morales and Julian Fierrez and Agata Lapedriza
• Abstract summary: This work explores facial expression bias as a security vulnerability of face recognition systems. We present a comprehensive analysis of how facial expression bias impacts the performance of face recognition technologies.
• Score: 73.85525896663371
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This work explores facial expression bias as a security vulnerability of face recognition systems. Despite the great performance achieved by state-of-the-art face recognition systems, the algorithms are still sensitive to a large range of covariates. We present a comprehensive analysis of how facial expression bias impacts the performance of face recognition technologies. Our study analyzes: i) facial expression biases in the most popular face recognition databases; and ii) the impact of facial expression in face recognition performances. Our experimental framework includes two face detectors, three face recognition models, and three different databases. Our results demonstrate a huge facial expression bias in the most widely used databases, as well as a related impact of face expression in the performance of state-of-the-art algorithms. This work opens the door to new research lines focused on mitigating the observed vulnerability.

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