Facial expression recognition based on shape and texture

被引：42
作者：
Xie, Xudong [1 ,2 ]
Lam, Kin-Man [1 ]
机构：
[1] Hong Kong Polytech Univ, Ctr Signal Proc, Elect & Informat Engn Dept, Hong Kong, Hong Kong, Peoples R China
[2] Tsinghua Univ, Dept Automat, Beijing, Peoples R China
来源：
PATTERN RECOGNITION | 2009年 / 42卷 / 05期
关键词：
Face recognition; Facial expression recognition; Elastic shape-texture matching; Spatially maximum occurrence model; Gabor wavelets; IMAGE SEQUENCES; FACE;
D O I：
10.1016/j.patcog.2008.08.034
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1003 / 1011
页数：9
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