Face Recognition Based on LFDA and LS-SVM
Qi Shen, Ruixiang Liu · 2009
Face recognition is one of the most challenging research topics in the field of pattern recognition and computer vision. To efficiently deal with this problem, a novel face recognition algorithm is proposed by the combination of local fisher discriminant analysis (LFDA) and least square version of SVM (LS-SVM). Experimental results on real face databases have demonstrated the better performance of the proposed algorithm.