Navigating the New Normal: A Bibliometric Exploration of Masked Face Recognition Research

Face recognition is a technique that has dominated several fields in the contemporary period, including security, surveillance, and biometric identity. The need for masked face recognition has increased, necessitating modifications to traditional algorithms due to the emergence of global health issues like the COVID-19 pandemic. This bibliometric study aims to thoroughly examine the research trends, significant contributions, and new directions in masked face recognition. Using the Scopus database, we identified pertinent papers over the previous ten years that showed a sharp increase in research activity after 2019. A developing multidisciplinary strategy that combines researchers in computer science, medical imaging, and public health was also seen in cooperation networks. The top institutions, authors, and nations in this field were selected to map the global distribution of research endeavors. Foreseeing future research directions, educating policymakers, and assisting stakeholders in negotiating the complications posed by masked people in facial recognition systems, the emerging themes and difficulties discussed here are essential. Our approach emphasizes the need for ongoing innovation in light of shifting cultural norms and technology environments.