中文摘要：

基于PCA人脸识别算法分为基于经验PCA（EPCA）算法和基于自适应PCA（APCA）算法．本文分析它们各自的构造原则和应用特点，借助3个公共人像数据库，用1个新构造的符号假设检验策略对它们进行客观的实验比较．比较结果显示，就整体性能而言，如果做EPCA训练的图像与样例图同身份，基于EPCA算法和基于APCA算法间差异很小，否则，差异很大．就可得的最优性能而言，两类算法间无显著差异．基于上述结论，文中分析和解答一些较有实际意义的问题，这为深入理解和合理使用基于PCA人脸识别算法提供有益参考．

英文摘要：

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.