A novel application of self-organizing network for facial expression recognition from radial encoded contours

Authors:
W. F. Gu;Y. V. Venkatesh;C. Xiang
Affiliations:
National University of Singapore, Department of Electrical and Computer Engineering, Singapore, Singapore;National University of Singapore, Department of Electrical and Computer Engineering, Singapore, Singapore;National University of Singapore, Department of Electrical and Computer Engineering, Singapore, Singapore
Venue:
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Pattern Recognition and Information Processing Using Neural Networks;Guest Editors: Fuchun Sun,Ying Tan,Cong Wang
Year:
2009

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Abstract

We propose an efficient algorithm for recognizing facial expressions using biologically plausible features: contours of face and its components with radial encoding strategy. A self-organizing network (SON) is applied to check the homogeneity of the encoded contours and then different classifiers, such as SON, multi-layer perceptron and K-nearest neighbor, are used for recognizing expressions from contours. Experimental results show that the recognition accuracy of our algorithm is comparable to that of other algorithms in the literature on the Japanese female facial expression database. We also apply our algorithm to Taiwanese facial expression image database to demonstrate its efficiency in recognizing facial expressions.