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ICB
2009
Springer
140views Biometrics» more  ICB 2009»
13 years 10 months ago
A Discriminant Analysis Method for Face Recognition in Heteroscedastic Distributions
Linear discriminant analysis (LDA) is a popular method in pattern recognition and is equivalent to Bayesian method when the sample distributions of different classes are obey to t...
Zhen Lei, ShengCai Liao, Dong Yi, Rui Qin, Stan Z....
ECCV
2006
Springer
14 years 5 months ago
Extending Kernel Fisher Discriminant Analysis with the Weighted Pairwise Chernoff Criterion
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
Guang Dai, Dit-Yan Yeung, Hong Chang
TASLP
2011
12 years 10 months ago
Time-Frequency Cepstral Features and Heteroscedastic Linear Discriminant Analysis for Language Recognition
Abstract—The shifted delta cepstrum (SDC) is a widely used feature extraction for language recognition (LRE). With a high context width due to incorporation of multiple frames, S...
Weiqiang Zhang, Liang He, Yan Deng, Jia Liu, M. T....
ICPR
2010
IEEE
13 years 6 months ago
A Discriminative and Heteroscedastic Linear Feature Transformation for Multiclass Classification
This paper presents a novel discriminative feature transformation, named full-rank generalized likelihood ratio discriminant analysis (fGLRDA), on the grounds of the likelihood ra...
Hung-Shin Lee, Hsin-Min Wang, Berlin Chen
ICIP
2003
IEEE
14 years 5 months ago
Boosting linear discriminant analysis for face recognition
In this paper, we propose a new algorithm to boost performance of traditional Linear Discriminant Analysis (LDA)-based face recognition (FR) methods in complex FR tasks, where hig...
Juwei Lu, Konstantinos N. Plataniotis, Anastasios ...