Exploring the facial expression perception-production link using real-time automated facial expression recognition

Motor production may play an important role in learning to recognize facial expressions. The present study explores the influence of facial production training on the perception of facial expressions by employing a novel production training intervention built on feedback from automated facial expression recognition. We hypothesized that production training using the automated feedback system would improve an individual's ability to identify dynamic emotional faces. Thirty-four participants were administered a dynamic expression recognition task before and after either interacting with a production training video game called the Emotion Mirror or playing a control video game. Consistent with the prediction that perceptual benefits are tied to expression production, individuals with high engagement in production training improved more than individuals with low engagement or individuals who did not receive production training. These results suggest that the visual-motor associations involved in expression production training are related to perceptual abilities. Additionally, this study demonstrates a novel application of computer vision for real-time facial expression intervention training.