Fusion of locally linear embedding and principal component analysis for face recognition (FLLEPCA)

Eimad Eldin Abusham, David Ngo, Andrew Teoh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We proposed a novel approach for face recognition to address the challenging task of recognition using a fusion of nonlinear dimensional reduction; Locally Linear Embedding (LLE) and Principal Component Analysis (PCA).LLE computes a compact representation of high dimensional data combining the major advantages of linear methods, With the advantages of non-linear approaches which is flexible to learn a broad of class on nonlinear manifolds. The application of LLE, however, is limited due to its lack of a parametric mapping between the observation and the low-dimensional output. In addition, the revealed underlying manifold can only be observed subjectively. To overcome these limitations, we propose our method for recognition by fusion of LLE and Principal Component Analysis (FLLEPCA) and validate their efficiency. Experiments on CMU AMP Face EXpression Database and JAFFE databases show the advantages of our proposed novel approach.

Original languageEnglish
Title of host publicationPattern Recognition and Image Analysis - 3rd International Conference on Advances in Pattern Recognition, ICAPR 2005, Proceedings
EditorsSameer Singh, Maneesha Singh, Chid Apte, Petra Perner
PublisherSpringer Verlag
Pages326-333
Number of pages8
ISBN (Print)9783540288336
DOIs
Publication statusPublished - 2005
Event3rd International Conference on Advances in Pattern Recognition, ICAPR 2005 - Bath, United Kingdom
Duration: 2005 Aug 222005 Aug 25

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3687 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Advances in Pattern Recognition, ICAPR 2005
Country/TerritoryUnited Kingdom
CityBath
Period05/8/2205/8/25

Bibliographical note

Funding Information:
This work is supported by the research Center of Multimedia

Funding Information:
This work is supported by the research Center of Multimedia University.

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2005.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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