基于二维非参数化判别分析的人脸识别

Human Face Recognition Based on Two Dimensional Nonparametric Discriminant Analysis

基于二维线性判别分析和非参数化判别分析的思想,提出了一种新颖的用于人脸识别的特征提取方法——二维非参数化判别分析方法.该方法解决了传统判别分析方法中的小样本问题与高斯分布假设问题.可以准确、高效地实现人脸识别.通过在ORL标准人脸数据库上的实验结果表明,算法相对于传统线性判别分析方法有显著优势.

A novel method for Human face recognition based on two dimensional nonparametric discriminant analysis is proposed. Traditional LDA-based methods suffer from some disadvantages such as small sample size problem（SSS）, course of a dimensionality, as well as a fundamental limitation resulting from the parametric nature of scatter matrices, based on the Gaussian distribution assumption. To address the problem, a new two dimensional nonparametric discriminant analysis is proposed and a new formulation of scatter matrices is given. Experimental results indicate the robustness and accuracy of the proposed method.