Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17016
Title: Facial expression recognition based on shape and texture
Authors: Xie, X
Lam, KM 
Keywords: Elastic shape-texture matching
Face recognition
Facial expression recognition
Gabor wavelets
Spatially maximum occurrence model
Issue Date: 2009
Publisher: Elsevier
Source: Pattern recognition, 2009, v. 42, no. 5, p. 1003-1011 How to cite?
Journal: Pattern recognition 
Abstract: In this paper, an efficient method for human facial expression recognition is presented. We first propose a representation model for facial expressions, namely the spatially maximum occurrence model (SMOM), which is based on the statistical characteristics of training facial images and has a powerful representation capability. Then the elastic shape-texture matching (ESTM) algorithm is used to measure the similarity between images based on the shape and texture information. By combining SMOM and ESTM, the algorithm, namely SMOM-ESTM, can achieve a higher recognition performance level. The recognition rates of the SMOM-ESTM algorithm based on the AR database and the Yale database are 94.5% and 94.7%, respectively.
URI: http://hdl.handle.net/10397/17016
ISSN: 0031-3203
EISSN: 1873-5142
DOI: 10.1016/j.patcog.2008.08.034
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