Abstract Purpose. This study performed a bibliometric analysis of global research on human facial recognition for forensic purposes, identifying trends in techniques, anatomical regions, and methodological evolution over five decades. Methods. Six databases (PubMed, Scopus, Web of Science, Embase, BVS, and Lilacs) were searched without language or year restrictions. We included studies focusing on human identification through clinical or imaging facial examinations. Data regarding year, journal, authors, keywords, age group, examination type, and methods (metric, morphological, or volumetric) were extracted. Two independent investigators used Rayyan™ for selection, and descriptive analysis was performed using VantagePoint™ and Excel™. Results. From 5016 identified articles, 424 studies published between 1970 and 2022 were included (four systematic reviews, three clinical, 377 observational, and 40 laboratory studies). Forensic Science International was the leading journal ( n = 113), and Stephan CN was the most prolific author. Photography was the most used examination ( n = 125). Metric analysis prevailed as the primary method ( n = 221). While the total face was the most frequent focus ( n = 239), the nose emerged as the most studied isolated region ( n = 20). Most studies ( n = 415) reported identification results. Conclusion. Facial identification research has grown significantly, with photography and metric methods remaining the current standards. However, bibliometric trends point toward a paradigm shift: the integration of Artificial Intelligence and 3D volumetric analysis is emerging as a critical frontier to overcome the limitations of conventional 2D techniques, offering superior precision and optimized forensic workflows.
Marques et al. (Fri,) studied this question.