Integrated Facial Identity Verification and Expression Intelligence Using Video Streams

Abstract

The increasing adoption of computer vision and artificial intelligence has created new opportunities for developing intelligent systems capable of understanding human facial behavior in real time. Facial expression analysis plays an important role in applications such as human– computer interaction, smart surveillance, healthcare monitoring, attendance management, and security systems. This paper presents a webcam-based facial expression detection and person recognition system that combines facial identification with emotion classification in a single framework. The proposed system first allows users to register by capturing facial images along with personal information and storing the extracted facial features in a trained recognition model. During real-time operation, the webcam continuously detects faces, identifies registered individuals, and predicts their facial expressions, such as happiness, sadness, anger, surprise, fear, disgust, and neutral state. The integration of face recognition and expression analysis enables simultaneous identification of the individual and interpretation of emotional responses without requiring manual intervention. The developed application provides a simple graphical interface for user registration, model training, and live expression recognition, making it suitable for practical deployment in educational institutions, workplaces, healthcare environments, and public monitoring systems. Experimental observations demonstrate that the proposed framework performs reliable real-time face detection and expression classification while maintaining efficient processing speed and recognition accuracy. The system offers a practical, scalable, and cost-effective solution for intelligent facial analysis using standard webcam devices.