Abstract

Facial recognition (FR) is an important subject in computer vision, evolving with the aid of deep learning and extensive datasets. End-to-end deep face recognition systems, which process natural images or video frames to generate facial features for identification. Convolutional Neural Networks (CNNs) operate at multiple resolutions, proving beneficial in monitoring closed environments such as classrooms, conferences, and events. In the realm of big data, the face recognition technology has expanded, especially in closed environments. Face recognition system in real-time proves useful for monitoring these closed settings. Two key considerations in face recognition include enhancing the accuracy of real-time face recognition and ensuring the stability of video processing systems. Through a comprehensive analysis, the face recognition system demonstrates an impressive accuracy rate, particularly valuable in closed environments.