基于改进的非负矩阵分解的人脸表情识别  

Facial Expression Recognition Based on Improved Non-negative Matrix Factorization

作　　者：田建华[1] TIAN Jian-hua（School of Distance Education,Heze University,Heze 274000,China）

机构地区：[1]菏泽学院远程教育学院,山东菏泽274000

出　　处：《电脑知识与技术》2011年第5期3105-3106,共2页Computer Knowledge and Technology

摘　　要：针对存在部分遮挡的人脸,提出了一种基于改进的非负矩阵分解的人脸表情识别方法,首先,用改进的非负矩阵分解算法对人脸图像进行表情特征提取,然后用最大相关分类器对面部表情进行分类。在Cohn-Kanade人脸表情数据库上的实验,结果表明,该方法提高了无遮挡的人脸表情识别,对有遮挡的人脸表情识别也有改善。This paper presented a facial expression recognition method based on improved non-negative matrix factorization with sub-region occlusion judgment.Given a still image containing facial expression information,expression feature vectors are extracted by non-negative matrix factorization firstly.Secondly,facial expressions are classified by using a maximum correlation classifier.Experiment on Cohn-Kanade facial expression database shows that the method improves the expression recognition for both non-occluded and partially occluded faces.

关 键 词：非负矩阵分解 特征提取 表情识别 部分遮挡 

分 类 号：TP391[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]