Facial gesture recognition using active appearance models based on neural evolution
Jorge García Bueno, Miguel González-Fierro, Luis E. Moreno, Carlos Balaguer · 2012
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.