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Emotion Mirror: A Novel Intervention for Autism Based on Real-Time Expression Recognition
David Deriso1, Joshua Susskind1, Lauren Krieger2, and Marian Bartlett1
1Institute for Neural Computation, University of California, San Diego, USA
deriso@gmail.com
jmsusskind@gmail.com
mbartlett@ucsd.edu
2Dept of Film, Television, and Digital Media, University of California, Los Angeles, USA
laurenkriegerart@gmail.com
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.
LNCS 7585, p. 671 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2012