TY - JOUR
T1 - Neighborhood Discriminant Nearest Feature Line Analysis and Its Application to Face Recognition
AU - Yan, Lijun
AU - Zheng, Weimin
AU - Chu, Shu-Chuan
AU - Roddick, John
PY - 2013
Y1 - 2013
N2 - In this paper, a novel subspace learning algorithm, called neighborhood discriminant nearest feature line analysis (NDNFLA), is proposed. NDNFLA aims to find the discriminant feature of samples by maximizing the between-class feature line (FL) scatter and minimizing the within-class FL scatter. At the same time, the neighborhood is preserved in the feature space. Experimental results demonstrate the efficiency of the proposed algorithm.
AB - In this paper, a novel subspace learning algorithm, called neighborhood discriminant nearest feature line analysis (NDNFLA), is proposed. NDNFLA aims to find the discriminant feature of samples by maximizing the between-class feature line (FL) scatter and minimizing the within-class FL scatter. At the same time, the neighborhood is preserved in the feature space. Experimental results demonstrate the efficiency of the proposed algorithm.
KW - Feature extraction
KW - Nearest feature line
KW - Subspace learning
UR - http://www.scopus.com/inward/record.url?scp=84883097307&partnerID=8YFLogxK
U2 - 10.6138/JIT.2013.14.1.13
DO - 10.6138/JIT.2013.14.1.13
M3 - Article
VL - 14
SP - 127
EP - 132
JO - Journal of Internet Technology
JF - Journal of Internet Technology
SN - 1607-9264
IS - 1
ER -