计算机应用研究2011，Vol.28Issue(4)：1536-1539,1543,5.DOI:10.3969/j.issn.1001-3695.2011.04.094
基于Gabor、Fisher脸多特征提取及集成SVM的人脸表情识别
Multiple features extraction using Gabor wavelet transformation, Fisher faces and integrated SVM with application to facial expression recognition
摘要
Abstract
Based on the static gray image expression database, this paper gave a recognition algorithm by using multiple facial expression features to construct multi-classifier.Aiming to improving speed of extracting features, features of expression that were extracted by local Gabor wavelet transformation on the selected facial landmark were used to constructing facial elastic templates.Extracted geometric features and Fisherfaces features on the facial effective area extracted by elastic templates.Primary integrated SVM should be constructed by combining with Geometric features; secondary integrated SVM should be constructed by combining with Fisherfaces features.Compared with the single features, the experimental results show that recognition rate and robustness are improved by experiments based on JAFFE and Cohn-Kanade.关键词
表情识别/改进的弹性模板/Gabor小波变换/Fisher脸/集成支持向量机/分类器级联Key words
expression recognition/ improved elastic templates/ Gabor wavelet transformation/ Fisherfaces/ integrated SVM/cascaded classifier分类
信息技术与安全科学引用本文复制引用
黄永明,章国宝,董飞,达飞鹏..基于Gabor、Fisher脸多特征提取及集成SVM的人脸表情识别[J].计算机应用研究,2011,28(4):1536-1539,1543,5.基金项目
国家自然科学基金资助项目(60805002) （60805002）
