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ICMCS
2006
IEEE
160views Multimedia» more  ICMCS 2006»
13 years 11 months ago
Selecting Kernel Eigenfaces for Face Recognition with One Training Sample Per Subject
It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...
Jie Wang, Konstantinos N. Plataniotis, Anastasios ...
PR
2006
127views more  PR 2006»
13 years 4 months ago
On solving the face recognition problem with one training sample per subject
The lack of adequate training samples and the considerable variations observed in the available image collections due to aging, illumination and pose variations are the two key te...
Jie Wang, Kostas N. Plataniotis, Juwei Lu, Anastas...
FGR
2011
IEEE
272views Biometrics» more  FGR 2011»
12 years 8 months ago
Adaptive discriminant analysis for face recognition from single sample per person
—Discriminant analysis, especially Fisherface and its numerous variants, have achieved great success in face recognition. However, these methods fail to work for face recognition...
Meina Kan, Shiguang Shan, Yu Su, Xilin Chen, Wen G...
IDEAL
2005
Springer
13 years 10 months ago
Weighted SOM-Face: Selecting Local Features for Recognition from Individual Face Image
Abstract. In human face recognition, different facial regions have different degrees of importance, and exploiting such information would hopefully improve the accuracy of the reco...
Xiaoyang Tan, Jun Liu, Songcan Chen, Fuyan Zhang
NIPS
1998
13 years 6 months ago
Facial Memory Is Kernel Density Estimation (Almost)
We compare the ability of three exemplar-based memory models, each using three different face stimulus representations, to account for the probability a human subject responded &q...
Matthew N. Dailey, Garrison W. Cottrell, Thomas A....