Real-Time Emotion Analysis with Python

A comprehensive analysis of facial emotion recognition systems utilizing Python and OpenCV is provided, focusing on methodologies, techniques, and algorithms for face detection, feature extraction, and emotion recognition, specifically using non-deep learning approaches. OpenCV's real-time facial detection and feature extraction capabilities are highlighted, making it suitable for applications in healthcare, security, and human-computer interaction. System performance is evaluated on benchmark datasets like FER2013. Key challenges, including limited accuracy, restricted evaluation across diverse datasets, and the recognition of only basic emotions, are addressed. The research emphasizes the strengths of these systems while identifying areas for improvement, aiming to optimize facial emotion recognition for more accurate, efficient, and generalizable solutions in real-world applications such as surveillance, emotional AI, and interactive systems.