Unveiling Emotions: A Survey on Face Recognition for behavioural analysis

Human behavior detection systems using face recognition technology have become one of the key areas of research in artificial intelligence and computer vision. The present study puts forward an all-encompassing framework for the detection and analysis of human behavior through face recognition, integrating advanced techniques in deep learning and pattern recognition. The proposed system integrates facial feature extraction, emotion recognition, and behavioral pattern analysis to provide a real-time glimpse into individual and group activities. Using CNNs and pretrained models, this system can give high accuracy rates in the emotions of happiness, sadness, anger, and surprise, which further correlate to certain behavioral states. The application area includes security surveillance, workplace monitoring, healthcare, and human-computer interaction. Experiments prove the system’s capability to learn and be appropriate under changing illumination, occlusions, and facial expressions and demonstrates robust performance. The work shows how face-based behavioral detection systems could lead the way to intelligent and context-aware applications.