Research on Adaptive Discriminative Analysis in Face Recognition with Single Sample per Person
Ding Xiufen · Video Engineering · 2014
Many traditional face recognition approaches fail to work with Single Sample per Person(SSPP),since they need more than one sample per person to estimate the within class scatter matrix.To address this problem,Adaptive Discriminant Analysis(ADA) is proposed in this paper.In this method,the within-class scatter matrix of each enrolled subject is estimated from his/her single sample,by inferring from a generic training set with multiple samples per person.Then,traditional methods are applied to extract features.Finally,experiments are finished on FERET and Yale face database by using KNN and Lasso regression classifier,which shows that proposed method has better recognition accuracy in addressing SSPP problem comparing with several latest approaches.