光电工程
光電工程
광전공정
OPTO-ELECTRONIC ENGINEERING
2007年
10期
83-87,144
,共6页
二维PCA%距离度量%矩阵体积度量%人脸识别
二維PCA%距離度量%矩陣體積度量%人臉識彆
이유PCA%거리도량%구진체적도량%인검식별
two dimensional PCA%distance measure%matrix volume measure%face recognition
本文提出一种符合高维几何空间理论的矩阵体积度量分类准则用于人脸识别.基于二维PCA的人脸识别方法主要研究的是特征提取部分,对后继的分类识别研究不多.基于二维PCA的人脸识别方法中典型的分类准则是比较特征向量的欧氏距离,而新方法比较的是矩阵的体积.在ORL和AR人脸库上的实验表明,所提出的矩阵体积度量较传统距离度量分类准则更有效.
本文提齣一種符閤高維幾何空間理論的矩陣體積度量分類準則用于人臉識彆.基于二維PCA的人臉識彆方法主要研究的是特徵提取部分,對後繼的分類識彆研究不多.基于二維PCA的人臉識彆方法中典型的分類準則是比較特徵嚮量的歐氏距離,而新方法比較的是矩陣的體積.在ORL和AR人臉庫上的實驗錶明,所提齣的矩陣體積度量較傳統距離度量分類準則更有效.
본문제출일충부합고유궤하공간이론적구진체적도량분류준칙용우인검식별.기우이유PCA적인검식별방법주요연구적시특정제취부분,대후계적분류식별연구불다.기우이유PCA적인검식별방법중전형적분류준칙시비교특정향량적구씨거리,이신방법비교적시구진적체적.재ORL화AR인검고상적실험표명,소제출적구진체적도량교전통거리도량분류준칙경유효.
A novel classification measure based on matrix volume according to the high dimensional geometry theory is proposed for face recognition. Many two dimensional PCA (2DPCA)-based face recognition methods almost pay much attention to the feature extraction, and the classification measure is little investigated. The typical classification measure used in 2DPCA is the sum of the Euclidean distance between two feature vectors in feature matrix, called traditional Distance Measure (DM). However, this proposed method is to compute the matrix volume. To test its performance,experiments are done based on ORL and AR face databases. The experimental results show the Matrix Volume Measure (MVM) is more efficient than the DM in 2DPCA-based face recognition.
