About

In our evolving digital landscape, face recognition technology is a powerful tool verifying the identities of individuals or categorizing groups of individuals with specific characteristics. However, the wide adoption of biometrics, including face recognition, has raised critical privacy concerns, mainly when the biometric matching process is conducted on centralized or untrusted servers. This need to protect individuals’ privacy and personal data calls for solutions implementing privacy-enhancing technologies, which is even more critical in Extended Reality (XR) environments. XR introduces a new dimension of data collection and interaction, often through headsets (e.g., head-mounted displays, HMDs) equipped with cameras and sensors. This increased level of data capture and management, combined with the immersive nature of XR, magnifies the risks to user privacy (e.g., continuous monitoring, intrusive data collection). Hence, implementing privacy-preserving measures becomes critical, not only to safeguard individuals’ sensitive information but also to foster trust, security, and ethical use of XR applications.

Considering that i) several techniques performing facial recognition have been proposed, ii) there is an increased interest in privacy-enhanced technologies and XR, and iii) there are specific EU legislations and regulations for data protection, privacy, and facial recognition, the burden falls into implementing facial recognition while safeguarding the rights to privacy and protection of personal data of individuals focused on XR. Hence, the challenge is to develop privacy-preserving facial recognition in XR for a series of different scenarios (e.g., individual identification, group categorization). This challenge is in line with the “Privacy-preserving facial recognition” challenge identified in the SERMAS project.