A linear discriminant analysis framework based on random subspace for face recognition

DOI10.1016/J.PATCOG.2006.12.002zbMath1118.68649OpenAlexW1996072998MaRDI QIDQ885218

Yunde Jia, Xiaoxun Zhang

Publication date: 8 June 2007

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2006.12.002

zbMATH Keywords

principal subspaceLDArandom subspace

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (5)

A fuzzy supervised learning method with dynamical parameter estimation for nonlinear discriminant analysis ⋮ Approximate polytope ensemble for one-class classification ⋮ An optimal symmetrical null space criterion of Fisher discriminant for feature extraction and recognition ⋮ Semi-supervised classification based on random subspace dimensionality reduction ⋮ A two-dimensional neighborhood preserving projection for appearance-based face recognition

Uses Software

• FERET

Cites Work

• Bagging, boosting and the random subspace method for linear classifiers
• A direct LDA algorithm for high-dimensional data -- with application to face recognition

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