Locally linear discriminant embedding: An efficient method for face recognition

DOI10.1016/J.PATCOG.2008.05.027zbMath1173.68673OpenAlexW2058232500MaRDI QIDQ948015

B. E. Eshmatov

Publication date: 8 October 2008

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

Full work available at URL: https://doi.org/10.1016/j.patcog.2008.05.027

zbMATH Keywords

feature extractionface recognitiondimensionality reductionmanifold learninglocally linear embedding

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (4)

Quantitative analysis of financial system fragility based on manifold curvature ⋮ Hierarchical analysis of Chinese financial market based on manifold structure ⋮ Distributed support vector machine in master-slave mode ⋮ Lp- and Ls-norm distance based robust linear discriminant analysis

Uses Software

• Yale Face
• CMU PIE

Cites Work

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• Principal component analysis.
• An efficient algorithm to solve the small sample size problem for LDA
• 10.1162/153244304322972667
• Structure Preserving Dimension Reduction for Clustered Text Data Based on the Generalized Singular Value Decomposition
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

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