Facial Expression Recognition based on EOG toward Emotion Detection for Human-Robot Interaction

Abstract

The ability of an intelligent system to recognize the user’s emotional and mental states is of considerable interest for human-robot interaction and human-machine interfaces. This paper describes an automatic recognizer of the facial expression around the eyes and forehead based on electrooculographic (EOG) signals. Six movements of the eyes, namely, up, down, right, left, blink and frown, are detected and reproduced in an avatar, aiming to analyze how they can contribute for the characterization of facial expression. The recognition algorithm extracts time and frequency domain features from EOG, which are then classified in real-time by a multiclass LDA classifier. The offline and online classification results showed a sensitivity around 92% and 85%, respectively.