@conference {64,
	title = {Learning to Make Facial Expressions},
	booktitle = {IEEE 8th International Conference on Development and Learning, 2009. ICDL 2009},
	year = {2009},
	month = {06/2009},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Shanghai},
	abstract = {<p><span style="color: rgb(68, 68, 68); font-family: {\textquoteright}Lucida Grande{\textquoteright}, Verdana, sans-serif; font-size: 14px;">This paper explores the process of self-guided learning of realistic facial expression production by a robotic head with 31 degrees of freedom. Facial motor parameters were learned using feedback from real-time facial expression recognition from video. The experiments show that the mapping of servos to expressions was learned in under one-hour of training time. We discuss how our work may help illuminate the computational study of how infants learn to make facial expressions.</span></p>
},
	keywords = {Actuators, Emotion recognition, face detection, face recognition, facial motor parameters, Feedback, Humans, learning (artificial intelligence), Machine Learning, Magnetic heads, Pediatrics, real-time facial expression recognition, Robot sensing systems, robotic head, Robots, self-guided learning, Servomechanisms, Servomotors},
	isbn = {978-1-4244-4117-4},
	author = {Wu, T. and Butko, N. and Ruvulo, P. and Bartlett, M. and Movellan, J.}
}