TY - GEN
T1 - Robust design of face recognition systems
AU - Yu, Sunjin
AU - Lee, Hyobin
AU - Kim, Jaihie
AU - Lee, Sangyoun
PY - 2006
Y1 - 2006
N2 - Currently, most face recognition methods provide a number of parameters to be optimized, leaving the selection and optimization of the right parameter set is necessary for the implementation. The choice of the right parameter set that is suitable for a rich enough class of input faces in pose and illumination variations is, however, quite difficult. We propose robust parameter estimation, using the Taguchi method, when applied to 2nd order mixture of eigenfaces method that allows effective (near optimal) performance under pose and illumination variations. A number of experimental results confirm the improvement (via robustness) vis-'a-vis conventional parameter estimation methods, and these methods promise a solution to the design of efficient parameter sets that support many multi-variable face recognition systems.
AB - Currently, most face recognition methods provide a number of parameters to be optimized, leaving the selection and optimization of the right parameter set is necessary for the implementation. The choice of the right parameter set that is suitable for a rich enough class of input faces in pose and illumination variations is, however, quite difficult. We propose robust parameter estimation, using the Taguchi method, when applied to 2nd order mixture of eigenfaces method that allows effective (near optimal) performance under pose and illumination variations. A number of experimental results confirm the improvement (via robustness) vis-'a-vis conventional parameter estimation methods, and these methods promise a solution to the design of efficient parameter sets that support many multi-variable face recognition systems.
UR - http://www.scopus.com/inward/record.url?scp=33745929333&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33745929333&partnerID=8YFLogxK
U2 - 10.1007/11751588_11
DO - 10.1007/11751588_11
M3 - Conference contribution
AN - SCOPUS:33745929333
SN - 3540340726
SN - 9783540340720
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 96
EP - 105
BT - Computational Science and Its Applications - ICCSA 2006
PB - Springer Verlag
T2 - ICCSA 2006: International Conference on Computational Science and Its Applications
Y2 - 8 May 2006 through 11 May 2006
ER -