Two-fold regularization for kernel Fisher discriminant analysis in face recognition

IEICE Electronics Express

Sang-Ki Kim¹  Kar-Ann Toh¹  Sangyoun Lee¹ 

[1] Department of Electrical and Electronic Engineering, Biometrics Engineering Research Center, Yonsei University

关键词: face recognition;    subspace learning;    kernel discriminant analysis;   

DOI  :  10.1587/elex.6.540

学科分类：电子、光学、磁材料

来源: Denshi Jouhou Tsuushin Gakkai

【 摘 要 】

References(6)Cited-By(1)Due to the inherent nature of kernel implementation, the kernel Fisher discriminant suffers from the small sample size problem. In this paper, we introduce a novel variant of the kernel Fisher discriminant formulation to circumvent this problem. By adopting a two-fold regularization scheme on the scatter matrices, we show both effectiveness and reliability of the proposed method particularly regarding the small sample size and the lack of dimensionality issues.

【 授权许可】

Unknown