机构地区: 五邑大学信息学院
出 处: 《五邑大学学报(自然科学版)》 2009年第3期28-31,36,共5页
摘 要: 提出了一种基于非负矩阵分解与支持向量机相结合的面部表情识别方法.使用直方图均衡化等方法对人脸图像进行预处理,使用非负矩阵分解算法进行表情特征提取,采用支持向量机对面部表情进行分类.以Matlab为仿真工具,在日本女性人脸表情数据库上测试,取得了66.19%的识别率. A novel approach to facial expression recognition based on the combination of Non-negative Matrix Factorization (NMF) and support vector machine (SVM) was proposed. First, the algorithm processed facial expression images with Histogram equalization operator. Then NMF method was used for feature dimension reduction and SVM for classification. Finally, the algorithm was implemented with Matlab and experimented in Japanese female facial expression database (JAFFE database). A recognition rate of 66.1% was obtained and the effectiveness of the proposed algorithm is proved.
领 域: [自动化与计算机技术] [自动化与计算机技术]