计算机工程2012，Vol.38Issue(6)：207-209,212,4.DOI:10.3969/j.issn.1000-3428.2012.06.068
基于Gabor小波和稀疏表示的人脸表情识别
Facial Expression Recognition Based on Gabor Wavelet and Sparse Representation
摘要
Abstract
By analyzing the biology background and mathematical properties of Gabor wavelet and sparse representation, a new approach for facial expression recognition based on Gabor wavelet and sparse representation is presented in this paper. Gabor wavelet transformation is adopted to extract features for the static facial expression image. The over-complete dictionary is constructed by the Gabor features of all training samples and sparse feature vector of this facial expression image is obtained by using sparse representation model. It uses a fusion recognition method for implementing multiple classifiers fusion. Experimental results show that integrating Gabor wavelet transformation and sparse representation is more effective for extracting expression image information. The approach effectively raises the accuracy of expression recognition.关键词
人脸表情识别/特征提取/稀疏表示/Gabor小波/融合识别/模糊密度Key words
facial expression recognition/ feature extraction/ sparse representation/ Gabor wavelet/ fusion recognition/ fuzzy density分类
信息技术与安全科学引用本文复制引用
张娟,詹永照,毛启容,邹翔..基于Gabor小波和稀疏表示的人脸表情识别[J].计算机工程,2012,38(6):207-209,212,4.基金项目
国家自然科学基金资助项目(61003183) （61003183）
江苏省自然科学基金资助项目(BK2009199) （BK2009199）
