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Null Space-Based Lda With Weighted Dual Personal Subspaces For Face  (Make Corrections)  
Recognition Xipeng Qiu and Lide Wu Media Computing Web Intelligence Lab...



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Abstract: Linear discriminant analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers the small sample size problem when dealing with the high dimensional face data. Moreover, the within-class and between-class scatter matrix used in LDA have low effective when dealing with face data of non-gaussian density. In this paper, we propose a new method for face recognition. We first calculate the weighted dual personal subspaces to replace the within and between... (Update)

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BibTeX entry:   (Update)

@misc{ qiu-null,
  author = "Recognition Xipeng Qiu",
  title = "Null Space-Based Lda With Weighted Dual Personal Subspaces For Face",
  url = "citeseer.ist.psu.edu/748125.html" }
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897   Introduction to statistical pattern recognition (context) - Fukunaga - 1990
495   Eigenfaces for recognition (context) - Turk, Pentland - 1991
124   Eigenfaces vs. Fisherfaces: Recognition using class specific.. - Belhumeur, Hespanda et al. - 1997
90   The feret database and evaluation procedure for face recogni.. (context) - Phillips, Wechsler et al. - 1998
77   Face recognition: A literature survey - Zhao, Chellappa et al. - 2003
41   Parameterisation of a stochastic model for human face identi.. - Samaria, Harter - 1994
16   Bayesian face recognition (context) - Moghaddam, Jebara et al. - 2000
11   A new LDAbased face recognition system which can solve the s.. (context) - Chen, Liao et al. - 2000
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