Some Researches for Face Recognition with One Training Image per Person
对单训练样本的人脸识别问题的研究

Nowadays many algorithms for face recognition are under the postulate that each person has many training images.There are few study with the one training sample per person.While each person may only provide one regis- tered photo in most cases.We solve this problem by add virtual images generating from the given training image,and study the differences of the recognition rates between PCA,Fisherface,(PC)~2 A and Two Dimension PCA(2DPCA).In this paper,a new 2DPCA which is based on the Maximum Margin Criterion is proposed.The average recognition rate on ORL face-databases achieves 75.28% only using one training image per person.