TY - GEN
T1 - Two-class linear discriminant analysis for face recognition
AU - Ekenel, Hazim Kemal
AU - Stiefelhagen, Rainer
PY - 2007
Y1 - 2007
N2 - In this paper, we present a novel face recognition system that uses two-class linear discriminant analysis for classification. In this approach a single M-class linear discriminant clussifier is divided into M two-class linear discriminant classifiers. This formulation provides many advantages like more discrimination between classes, simpler calculation of projection vectors and easier update of the database with new individuals. We tested the proposed algorithm on the CMU PIE and Yale face databases. Significant performance improvements are observed, especially when the number of individuals to be classified increases.
AB - In this paper, we present a novel face recognition system that uses two-class linear discriminant analysis for classification. In this approach a single M-class linear discriminant clussifier is divided into M two-class linear discriminant classifiers. This formulation provides many advantages like more discrimination between classes, simpler calculation of projection vectors and easier update of the database with new individuals. We tested the proposed algorithm on the CMU PIE and Yale face databases. Significant performance improvements are observed, especially when the number of individuals to be classified increases.
UR - http://www.scopus.com/inward/record.url?scp=50249142970&partnerID=8YFLogxK
U2 - 10.1109/SIU.2007.4298761
DO - 10.1109/SIU.2007.4298761
M3 - Conference contribution
AN - SCOPUS:50249142970
SN - 1424407192
SN - 9781424407194
T3 - 2007 IEEE 15th Signal Processing and Communications Applications, SIU
BT - 2007 IEEE 15th Signal Processing and Communications Applications, SIU
T2 - 2007 IEEE 15th Signal Processing and Communications Applications, SIU
Y2 - 11 June 2007 through 13 June 2007
ER -