Regularized Linear Discriminant Analysis for Face Recognition Based on Ensemble Learning
Cao Zhen-tian · Jisuanji gongcheng · 2010
For dealing with the Small Sample Size(SSS) problem in face recognition tasks,regularized Linear Discriminant Analysis(LDA) based on ensemble learning is proposed.By using Adaboost method,weighting function is introduced into the samples,which is closer in the output space in each iteration.So that the separability between these classes is enhanced in the new feature subspace,and the recognition rate is also improved to 98.5%.Experimental results on facial database of ORL show that this method achieves better performance than traditional methods do.