A Facial Expression Based Continuous Emotional State Monitoring System with GPU Acceleration

Automatic detection and analysis of the emotional states provide important clues for predicting personal behaviors. The techniques are essential for monitoring and protecting such vulnerable people as patients with mental health conditions, persons under heavy stress, and young kids with neurodevelopmental disorders. However, few automatic emotional state recognition systems have been put into real-world applications. Among various reasons leading the lack of success, the overwhelming computing complexity is a major hurdle. In this paper, a continuously emotional state monitoring system that is capable of recognizing naturalistic facial expression in realtime is designed and implemented on a desktop PC with GPU as an accelerator. It has been tested in real scenarios and the experimental results prove promising.