Understanding the techniques and methods for real-time face recognition and tracking: A comprehensive survey

A real-time facial recognition and tracking system has been developed that includes functions for detecting and tracking faces in real time and allows local images to be uploaded for face comparison. Its key advantage is the ability to instantly analyze captured facial images and identify recognized individuals without delay. The paper aims to survey previous research on real-time facial recognition and tracking to better understand the techniques and methods used in this field. Assessing and comparing other research enhances the picture of both the strong and weak points of that research and the chances for development. It can be a source of information for designing the upcoming technologies for the increasing precision of the existing technologies utilized in the real-time face recognition and tracking. The study discusses the applications of various artificial intelligence, machine learning, and convolutional neural network techniques for the specific aim of accurate and speedy facial identification, particularly in the case of multiple faces. Lastly, there is the tabular presentation of the differences between the techniques together with the methods of previous researchers. This survey can help identify current and future face recognition and tracking trends. The paper provides insights into the challenges and processes involved in real-time face recognition and tracking and can help researchers and developers in this field.