Navigating the New Normal: A Bibliometric Analysis of Masked Face Recognition Research Using VOSviewer and Biblioshiny

Face recognition is a technique that has dominated in several fields such as security, surveillance, and biometric identity. However, the recent global health crisis, particularly the COVID-19 pandemic, has led to a growing need for face recognition systems that can accurately identify people even when they are wearing masks. This bibliometric study utilizes VOSviewer and Biblioshiny to conduct a comprehensive analysis of masked face recognition research trends from 2018 to 2024. The study focused on understanding the recent developments in masked face recognition research. By searching Scopus database, we found a significant increase in research activity on this topic starting around 2019. This increase is likely due to the COVID-19 pandemic, which made it more important to develop technology that can identify people even when they are wearing masks. We identified the top institutions, authors, and countries contributing to this research and the dominant themes and collaborations. Our findings demonstrate a 250% increase in publications from 2019 to 2024, focusing on deep learning techniques and pandemic-specific applications. Network analysis identified the Fraunhofer Institute and Chinese universities as key players in the field. These results provide clear view into the global distribution of research efforts, the evolution of masked face recognition technology, and its societal impacts, offering a foundation for future innovation and policy development. © 2024 Slovene Society Informatika. All rights reserved.