Facial Features Approximation for Expression Detection in Human-Robot Interface

This paper presents a facial expression recognition system employing Bézier curves approximation technique. The system is based on facial features extraction using the knowledge of the face geometry and approximated by 3rd order Bézier curves representing the relationship between the motion of features and changes of expressions. For face detection, color segmentation based on the novel idea of fuzzy classification has been employed that manipulates ambiguity in colors. Experimental results demonstrate that this method can recognize the facial expressions with an accuracy of more than 90% in all cases. Finally the system has been implemented using a manipulator robot and issuing facial expression commands.