Face Linear Discriminant Analysis Based on Graph Embedding and Regularization
Peng Hu · Jisuanji gongcheng · 2011
This paper proposes a new Linear Discriminant Analysis(LDA) for face recognition based on the graph embedding and regularization. The unsupervised optimal class separate criterion is built,and it proposes a method to get this projection vector on the graph embedding frame.It can get a huge save of computational consumption and utilize the class information of samples more effectively.Experimental results demonstrate the effectiveness and efficiency of this method.