二维非参数化判别分析方法中的人脸识别算法研究

在使用传统线性判别分析方法计算类间散射矩阵时,使用类中心来近似表示各个类,类内散射矩阵的定义有一定的局限性,从而导致算法性能不稳定、小样本、数据的高斯分布假设及维数困扰等问题.提出了一种用于人脸识别的二维非参数化判别分析方法,对类间散射度矩阵和类内散射度矩阵进行了重新定义,考虑了各类数据的边界结构.通过在ORL标准人脸数据库上的实验结果,验证了算法相对于传统算法的鲁棒性和准确率.

Research on Two Dimensional Nonparametric Discriminant Analysis for Face Recognition

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