Locality Embedding Projection and Its Application to Face Recognition
Caikou Chen · Jisuanji gongcheng · 2011
A main defect of Linear Discriminant Analysis(LDA) is that local geometric features are ignored.To address this problem,a novel manifold-based method named Locality Embedding Projection(LEP) algorithm is presented in this paper.In the algorithm,neighborhood relationship and class label information are used to classify training sample set.For each training sample,there are two classes which are called neighbor class and non-neighbor class;then inter-class scatter and intra-class scatter are defined for each training sample.The ratio of total inter-class scatter and total intra-class scatter is maximized to make nearby samples with the same class-label are more compact,and nearby classes are separated.Experimental results on ORL and FERET face databases show effectiveness of the proposed method.