Facial gesture recognition using active appearance models based on neural evolution

Authors:
Jorge Garcíia Bueno;Miguel González-Fierro;Luis Moreno;Carlos Balaguer
Affiliations:
Robotics Lab, Madrid, Spain;Robotics Lab, Madrid, Spain;Robotics Lab, Madrid, Spain;Robotics Lab, Madrid, Spain
Venue:
HRI '12 Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction
Year:
2012

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Abstract

Facial gesture recognition is one of the main topics in HRI. We have developed a novel algorithm who allows to detect emotional states, like happiness, sadness or emotionless. A humanoid robot is able to detect these states with a ratio of success of 83% and interact in consequence. We use Active Appearance Models (AAMs) to determinate face features and classify the emotions using neural evolution, based on neural networks and differential evolution algorithm.