A comparison of three methods of face recognition for home photos
Che-Hua Yeh, Pei-Ruu Shih, Yin-Tzu Lin, Kuan-Ting Liu, Huang-Ming Chang, Ming Ouhyoung · 2009
This poster presents experimental results of three face recognition methods -- Support Vector Machine (SVM), Local Binary Pattern (LBP)-based, and Sparse Represented-based Classification (SRC). We will show the experimental results based on AR face database and on home photos. The experiments show that the three algorithms can achieve over 85% recognition rate in AR database. However, the recognition rate is extremely reduced in home photos. SVM and SRC-based method encounter challenges of selecting training model while LBP-based method encounters the challenge of merging over scattered clusters. Our goal is to improve the accuracy and efficiency especially in home photos based on the three methods.