A Bibliometric Analysis on Face Recognition Technology Research

Face recognition is a biological technology based on identity recognition of human face feature information. In this study, Web of Science Core Collection database is used as data source. Using Excel, Bibexcel and VOSviewer software for data mining and quantitative analysis of the 1980-2018 year research papers on face recognition, we explores the trend of change, the distribution of research forces, key areas, research hot spots and international cooperation. The results show that the number of documents in face recognition has been growing, and there are many subjects involved in the research of face recognition technology, mainly Computer Science, Enginerring and Psychology. There are many research papers on face recognition in China and the United States; China is most prominent in international cooperation and has strong cooperative relations with all major countries; the Chinese Academy of Sciences is very active in the research of face recognition, and its papers are far ahead of other institutions. The main focuses of the study are feature extraction, face detection, sparse representation, face perception, etc. The main hot spots of research are sparse representation, dictionary learning, deep learning, semisupervised learning, metric learning, sparse coding, etc.