TY - GEN
T1 - Tuning kernel parameters with different gabor features for face recognition
AU - Shen, Linlin
AU - Ji, Zhen
AU - Bai, Li
PY - 2007
Y1 - 2007
N2 - Kernel methods like support vector machine, kernel principal component analysis and kernel fisher discriminant analysis have recently been successfully applied to solve pattern recognition problems such as face recognition. However, most of the papers present the results without giving kernel parameters, or giving parameters without any explains. In this paper, we present an experiments based approach to optimize the performance of a Gabor feature and kernel method based face recognition system. During the process of parameter tuning, the robustness of the system against variations of kernel function, kernel parameters and Gabor features are extensively tested. The results suggest that the kernel method based approach, with tuned parameters, achieves significantly better results than other algorithms available in literature.
AB - Kernel methods like support vector machine, kernel principal component analysis and kernel fisher discriminant analysis have recently been successfully applied to solve pattern recognition problems such as face recognition. However, most of the papers present the results without giving kernel parameters, or giving parameters without any explains. In this paper, we present an experiments based approach to optimize the performance of a Gabor feature and kernel method based face recognition system. During the process of parameter tuning, the robustness of the system against variations of kernel function, kernel parameters and Gabor features are extensively tested. The results suggest that the kernel method based approach, with tuned parameters, achieves significantly better results than other algorithms available in literature.
KW - Gabor features
KW - Kernel methods
UR - http://www.scopus.com/inward/record.url?scp=38049081152&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-74205-0_91
DO - 10.1007/978-3-540-74205-0_91
M3 - Conference contribution
AN - SCOPUS:38049081152
SN - 9783540742012
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 881
EP - 890
BT - Advanced Intelligent Computing Theories and Applications
PB - Springer Verlag
T2 - 3rd International Conference on Intelligent Computing, ICIC 2007
Y2 - 21 August 2007 through 24 August 2007
ER -