A real time and robust facial expression recognition and imitation approach for affective human-robot interaction using Gabor filtering

• Published in: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 2188 - 2193
• Main Authors: Cid, Felipe, Prado, Jose Augusto, Bustos, Pablo, Nunez, Pedro
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-11-2013
• Subjects: Bayes methods; Face recognition; Facial features; Feature extraction; Image edge detection; Robustness
• ISSN: 2153-0858; 2153-0866
• DOI: 10.1109/IROS.2013.6696662

Facial expressions are a rich source of communicative information about human behavior and emotion. This paper presents a real-time system for recognition and imitation of facial expressions in the context of affective Human Robot Interaction. The proposed method achieves a fast and robust facial feature extraction based on consecutively applying filters to the gradient image. An efficient Gabor filter is used, along with a set of morphological and convolutional filters to reduce the noise and the light dependence of the image acquired by the robot. Then, a set of invariant edge-based features are extracted and used as input to a Dynamic Bayesian Network classifier in order to estimate a human emotion. The output of this classifier updates a geometric robotic head model, which is used as a bridge between the human expressiveness and the robotic head. Experimental results demonstrate the accuracy and robustness of the proposed approach compared to similar systems.