Please use this identifier to cite or link to this item: https://doi.org/10.1007/s00500-009-0441-1
Title: A novel application of self-organizing network for facial expression recognition from radial encoded contours
Authors: Gu, W.F.
Venkatesh, Y.V. 
Xiang, C. 
Keywords: Facial contours
Facial expression recognition
Radial encoding
Self-organizing network
Issue Date: 2010
Citation: Gu, W.F., Venkatesh, Y.V., Xiang, C. (2010). A novel application of self-organizing network for facial expression recognition from radial encoded contours. Soft Computing 14 (2) : 113-122. ScholarBank@NUS Repository. https://doi.org/10.1007/s00500-009-0441-1
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. © Springer-Verlag 2009.
Source Title: Soft Computing
URI: http://scholarbank.nus.edu.sg/handle/10635/50848
ISSN: 14327643
DOI: 10.1007/s00500-009-0441-1
Appears in Collections:Staff Publications

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