Facial Behaviour

Facial behavior analysis focuses on understanding human emotions and mental states through the observation and interpretation of facial expressions, including subtle cues like gaze and head pose. Current research employs machine learning models, often incorporating deep learning architectures like transformers and convolutional neural networks, to analyze both posed and spontaneous facial expressions, often integrating audio and physiological signals (e.g., EEG) for improved accuracy. This field is significant for advancing human-computer interaction, particularly in robotics and virtual agent development, as well as for clinical applications in diagnosing and monitoring affective disorders, offering objective and potentially faster diagnostic tools.