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基于局部二元模式的面部表情识别研究 被引量：3

Facial expression recognition research based on local binary pattern
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摘要 提出了一种基于局部二元模式(Local Binary Pattern,LBP)与支持向量机(SVM)相结合的面部表情识别方法。使用LBP算子对图像进行处理,对图像的模式进行统计形成面部表情特征;使用线性判别分析对表情特征进行降维处理;采用支持向量机对面部表情进行分类。用Matlab实现了上述方法,并在日本女性人脸表情(JAFFE)数据库上测试,取得了70.95%的识别率。 A novel approach to facial expression recognition based on the combination of Local Binary Pattern（LBP） and Support Vector Machine（SVM） is proposed.First,the algorithm processes facial expression images with LBP operator and then facial expression features are formed by statistics of image＇s LBPs.Then Linear Discrimination Analysis（LDA） method is used for feature di- mension reduction and SVM for classification.Finally,the algorithm is implemented with Matlab and experimented in Japanese Female Facial Expression database（JAFFE database ）.A recognition rate of 70.95% is obtained and shows the effectiveness of the proposed algorithm.
作者 应自炉 方谢燕
机构地区 五邑大学信息学院 北京航空航天大学电子信息工程学院
出处 《计算机工程与应用》 CSCD 北大核心 2009年第29期180-183,共4页 Computer Engineering and Applications
基金 广东省自然科学基金(No.07010869) 北京大学视觉与听觉信息处理国家重点实验室开放课题基金项目(No.0505) 浙江大学CAD&CG国家重点实验室开放课题(No.A0703)~~
关键词 面部表情识别 局部二元模式 线性判别分析 支持向量机 facial expression recognition Local Binary Pattern （LBP） Linear Discrimination Analysis （LDA） Support Vector Machine（SVM）
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献8

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二级参考文献12

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共引文献47

同被引文献37

  • 1徐正光,闫恒川,张利欣.基于表情识别的独立成分分析方法的研究[J].计算机工程,2006,32(24):183-185. 被引量：8
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  • 5Shan CF, Gong SGB, Peter W. McOwanFacial expression recognition based on Local Binary Pattems:a comprehensive study. Image and Vision Computing 2009,27:803-816.
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引证文献3

二级引证文献16

计算机工程与应用
2009年 第29期

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