TY - GEN
T1 - Learning KPCA for face recognition
AU - Hao, Wangli
AU - Li, Jianwu
AU - Zhang, Xiao
PY - 2013
Y1 - 2013
N2 - Kernel principal component analysis (KPCA) is an effective method for face recognition. However, the expression of its final solution needs to take advantage of all training examples, such that its run in real-world application with large scale training set is time-consuming. This paper proposes to apply radial basis function neural network (RBFNN) to learn the feature extraction process of KPCA in order to improve the running efficiency of KPCA-based face recognition system. Experimental results based on two different face benchmark data sets, including ORL and UMIST, show that the proposed method can approach to the recognition accuracy of the original KPCA, but have sparser solutions. The proposed method can be applied to real-time or online face recognition systems.
AB - Kernel principal component analysis (KPCA) is an effective method for face recognition. However, the expression of its final solution needs to take advantage of all training examples, such that its run in real-world application with large scale training set is time-consuming. This paper proposes to apply radial basis function neural network (RBFNN) to learn the feature extraction process of KPCA in order to improve the running efficiency of KPCA-based face recognition system. Experimental results based on two different face benchmark data sets, including ORL and UMIST, show that the proposed method can approach to the recognition accuracy of the original KPCA, but have sparser solutions. The proposed method can be applied to real-time or online face recognition systems.
KW - Face recognition
KW - Kernel principal component analysis
KW - Radial basis function neural network
UR - http://www.scopus.com/inward/record.url?scp=84901501106&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-39678-6_24
DO - 10.1007/978-3-642-39678-6_24
M3 - Conference contribution
AN - SCOPUS:84901501106
SN - 9783642396779
T3 - Communications in Computer and Information Science
SP - 142
EP - 146
BT - Emerging Intelligent Computing Technology and Applications - 9th International Conference, ICIC 2013, Proceedings
PB - Springer Verlag
T2 - 9th International Conference on Intelligent Computing, ICIC 2013
Y2 - 28 July 2013 through 31 July 2013
ER -