期刊论文

Margin discriminant projection and its application in expression recognition

中文

计算机应用

1001-9081

2017

37

5

1413-1418

10.11772/j.issn.1001-9081.2017.05.1413

(13BTQ050):the National Social Science Foundation of China (13BTQ050):国家社会科学基金资助项目

本校为第一机构

针对全局降维方法判别信息不足,局部降维方法对邻域关系的判定存在缺陷的问题,提出一种新的基于间距的降维方法——间距判别投影(MDP)。首先,根据类的中心均值的异类近邻关系定义描述类边缘的边界向量;在这个基础上,MDP重新定义类间离散度矩阵,同时,使用全局的方法构造类内离散度矩阵;然后,MDP借鉴判别分析思想建立衡量类间距的准则,并通过类间距最大化增强样本在投影空间中的可分性。对MDP在人脸表情数据库JAFFE和Extended Cohn-Kanade上进行表情识别实验,并且跟传统的降维方法主成分分析(PCA)、最大间距准则(MMC)和边界Fisher分析(MFA)进行对比,实验结果表明,所提算法能够有效提取更具区分性的...

Considering that global dimensionality reduction methods lack useful discriminant information, and local dimensionality reduction methods have defects in measuring neighborhood relationships, a novel dimensionality reduction method based on margin, named Margin Discriminant Projection （MDP）, was proposed. Depending on the neighbor structure of mean vector of classes, the boundary vector of the class edge was defined by the heterogeneous neighbor relation of the center mean of the class. On this basis, the between-class scatter matrix was rede...