Face Detection: Present State and Research Directions

Locating human faces in digital photos is done using a face detection algorithm, which is based on artificial intelligence (AI). Facial detection technology makes real-time surveillance and tracing of persons feasible in a variety of fields, including security, biometrics, law enforcement, entertainment, and personal security [1]. Face detection has progressed from traditional computer vision methods to more sophisticated artificial neural networks (ANNs) and associated technologies, with the ultimate result being a steady improvement in performance. It is the foundation for several important applications, including face tracking, face analysis, and face recognition. Face detection helps with facial analysis by helping to select which areas of an image or video to focus on to identify age, gender and emotion from facial expressions. Face detection data is necessary for algorithms that determine which elements of an image or video are necessary to create a facial print in a facial recognition system that mathematically maps an individual's facial features and stores the data as a face print. If a new facial print is discovered, it can be compared to facial prints that have already been stored to see if there is a match. Figure 1 shows different face detection techniques. Major contributions of this paper are a brief, yet comprehensive review of the approaches and advances in the field of face detection; and a list of challenges and research directions.