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FGR
2004
IEEE

Intra-Personal Kernel Space for Face Recognition

14 years 2 months ago
Intra-Personal Kernel Space for Face Recognition
Intra-personal space modeling proposed by Moghaddam et. al. has been successfully applied in face recognition. In their work the regular principal subspaces are derived from the intra-personal space using a principal component analysis and embedded in a probabilistic formulation. In this paper, we derive the principal subspace from the intra-personal kernel space by developing a probabilistic analysis of kernel principal components for face recognition. We test this new algorithm on a subset of the FERET database with illumination and facial expression variations. The recognition performance demonstrates its advantage over other traditional subspace approaches.
Shaohua Kevin Zhou, Rama Chellappa, Baback Moghadd
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2004
Where FGR
Authors Shaohua Kevin Zhou, Rama Chellappa, Baback Moghaddam
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