Facial Expression Recognition for Human-Robot Interaction

Abstract

Facial expression recognition (FER) has been applied for human-robot interaction (HRI). An assistant robot having a close interaction with human being should be able to recognize human facial expression. FER is a non-trivial problem because each individual has his own way to reveal his emotion and the facial expressions of two different persons may not be totally identical. Facial expression can be divided into four phases: neutral, onset, apex, offset, and then back to neutral. In this paper, we propose a hybrid method to recognize the facial expression in the apex phase. In the 1 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">st</sup> stage, we use Gabor filter to obtain the facial features and apply Support Vector Machine (SVM) to identify Action Units (AUs). In the 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> stage, based on the identified AUs, we apply random forest classifiers to recognize the facial expressions. Finally, we show the experimental results and compare our method with the other methods.