MPCA on gabor tensor for face recognition

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1 Scopus citations

Abstract

There is a growing interest in subspace learning techniques for face recognition. This paper proposes a novel face recognition method based on MPCA with Gabor tensor representation. Although the Gabor face representation has achieved great success in face recognition, the excessive dimension of the data space often brings the algorithms into the curse of dimensionality dilemma. In this paper, we propose a 3rd-order Gabor tensor representation derived from a complete response set of 40 Gabor filters. Then MPCA (Multi-linear Principal Component Analysis) is applied to each Gabor tensor 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 ORL database show promising results of the proposed method.

Original languageEnglish
Title of host publicationProceedings of the 2015 Chinese Intelligent Automation Conference - Intelligent Information Processing
EditorsZhidong Deng, Hongbo Li
PublisherSpringer Verlag
Pages421-429
Number of pages9
ISBN (Print)9783662464687
DOIs
StatePublished - 2015
Externally publishedYes
EventChinese Intelligent Automation Conference, 2015 - Fuzhou, China
Duration: 1 Jan 2015 → …

Publication series

NameLecture Notes in Electrical Engineering
Volume336
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceChinese Intelligent Automation Conference, 2015
Country/TerritoryChina
CityFuzhou
Period1/01/15 → …

Keywords

  • Face recognition
  • Gabor tensor
  • MPCA
  • Representation

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