Comparison between Two Kinds of PCA-Based Face Recognition Algorithmsby Sign Hypothesis Testing Strategy
LI Le, ZHANG Yu-Jin
Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084 Department of Electronic Engineering, Tsinghua University, Beijing 10084
Abstract PCA-based face recognition algorithms are actually classified into adaptive PCA based (APCA-based) algorithms and empirical PCA-based (EPCA-based) algorithms. The design principles and application characteristics of these two kinds of algorithms are analyzed. A new sign hypothesis testing strategy is designed to make objective comparisons between them on three common face databases. Two basic conclusions are drawn according to the comparison results. On one hand, as far as holistic performance is concerned, the difference between EPCA-based algorithms and APCA-based algorithms is relatively small if the training images have the same identity set as the gallery ones. Otherwise, the difference between them is very large. On the other hand, as far as the best realizable performance is concerned, there is no significant difference between them. Thus, some practical problems are analyzed and resolved. The conclusion provides a useful reference for deeply understanding and reasonably using PCA-based face recognition algorithms.
LI Le,ZHANG Yu-Jin. Comparison between Two Kinds of PCA-Based Face Recognition Algorithmsby Sign Hypothesis Testing Strategy[J]. , 2008, 21(4): 432-440.
2008, Vol. 21 
