Facial Emotion Recognition and Adaptative Postural Reaction by a Humanoid based on Neural Evolution

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Description

We present a method of bidirectional interaction between a human and a humanoid robot in terms of emotional expressions. The robot is able to detect continuous transitions of human emotions that ranges from very sad to very happy using Active Appearance Models (AAMs) and Neural Evolution Algorithm to determinate the face shape and gestures. As a response of the
human emotions, the robot performs postural reactions that dynamically adapt to the human expressions, performing a body language which changes in terms of intensity as the human emotions vary. Our method is implemented in the HOAP-3 humanoid robot.
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