Facial expression recognition based on local binary patterns

被引：52

作者：

Feng X. ^{[1
]}

Pietikäinen M. ^{[2
]}

Hadid A. ^{[2
]}

机构：

[1] Northwestern Polytechnic University, Xi'an

[2] Department of Electrical and Information Engineering, Machine Vision Group, University of Oulu, FIN-90014

来源：

Pattern Recogn. Image Anal. | 2007年 / 4卷 / 592-598期

关键词：

Feature Vector; Feature Selection; Facial Expression; Face Image; Local Binary Pattern;

D O I：

10.1134/S1054661807040190

中图分类号：

学科分类号：

摘要：

In this paper, a novel approach to automatic facial expression recognition from static images is proposed. The face area is first divided automatically into small regions, from which the local binary pattern (LBP) histograms are extracted and concatenated into a single feature histogram, efficiently representing facial expressions-anger, disgust, fear, happiness, sadness, surprise, and neutral. Then, a linear programming (LP) technique is used to classify the seven facial expressions. Experimental results demonstrate an average expression recognition accuracy of 93.8% on the JAFFE database, which outperforms the rate of all other reported methods on the same database. © 2007 Pleiades Publishing, Ltd.

引用

页码：592 / 598

页数：6

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