Presentation-level Privacy Protection Techniques for Automated Face Recognition—A Survey

Abstract

The use of Biometric Facial Recognition (FR) systems have become increasingly widespread, especially since the advent of deep neural network-based architectures. Although FR systems provide substantial benefits in terms of security and safety, the use of these systems also raises significant privacy concerns. This article discusses recent advances in facial identity hiding techniques, focusing on privacy protection approaches that hide or protect facial biometric data before camera devices capture the data. Moreover, we also discuss the state-of-the-art methods used to evaluate such privacy protection techniques. The primary motivation of this survey is to assess the relative performance of facial privacy protection methods and identify open challenges and future work that needs to be considered in this research area.