Emotion Mirror: A Novel Intervention for Autism Based on Real-Time Expression Recognition

Abstract

Facial expression perception and production are crucial for social functioning. Children with autism spectrum disorders (ASD) are impaired in their ability to produce and perceive dynamic facial expressions, which may contribute to social deficits. Here we present a novel intervention system for improving facial expression perception and production in children with ASD based on computer vision. We present a live demo of the Emotion Mirror, a game where the children make facial expressions of basic emotions (anger, disgust, fear, happiness, sadness, and surprise) that are “mirrored” by a cartoon character on the screen who responds dynamically in real-time. In the reverse mirror condition, the character makes an expression and children are rewarded when they successfully copy the expression of the character. This application demonstrates a novel intersection of computer vision and medicine enabled by real-time facial expression processing.