Face recognition by discriminant analysis with Gabor tensor representation

Zhen Lei, Rufeng Chu, Ran He, Shengcai Liao, Stan Z. Li

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

27 Citations (Scopus)

Abstract

This paper proposes a novel face recognition method based on discriminant analysis with Gabor tensor representation. Although the Gabor face representation has achieved great success in face recognition, its huge number of features often brings about the problem of curse of dimensionality. In this paper, we propose a 3rd-order Gabor tensor representation derived from a complete response set of Gabor filters across pixel locations and filter types. 2D discriminant analysis is then applied to unfolded tensors to extract three discriminative subspaces. The dimension reduction is done in such a way that most useful information is retained. The subspaces are finally integrated for classification. Experimental results on FERET database show promising results of the proposed method.

Original languageEnglish
Title of host publicationAdvances in Biometrics - International Conference, ICB 2007, Proceedings
PublisherSpringer Verlag
Pages87-95
Number of pages9
ISBN (Print)9783540745488
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event2007 International Conference on Advances in Biometrics, ICB 2007 - Seoul, Korea, Republic of
Duration: Aug 27 2007Aug 29 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4642 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2007 International Conference on Advances in Biometrics, ICB 2007
Country/TerritoryKorea, Republic of
CitySeoul
Period8/27/078/29/07

Keywords

  • Discriminant analysis
  • Face recognition
  • Gabor tensor representation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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