Two dimensional Laplacianfaces method for face recognition

Niu Ben, Chi Keung Simon Shiu, Sankar Kumar Pal

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

In this paper we propose the two dimensional Laplacianfaces method for face recognition. The new algorithm is developed based on the two techniques, i.e., locality preserved embedding and image based projection. The two dimensional Laplacianfaces method is not only computationally more efficient but also more accurate than the one dimensional Laplacianfaces method in extracting the facial features for human face authentication. Extensive experiments are performed to test and evaluate the new algorithm using the Yale and the AR face databases. The experimental results indicate that the two dimensional Laplacianfaces method significantly outperforms the existing two dimensional Eigenfaces, the two dimensional Fisherfaces and the one dimensional Laplacianfaces methods under the various settings of experiment conditions.
Original languageEnglish
Title of host publicationRough Sets and Current Trends in Computing - 5th International Conference, RSCTC 2006, Proceedings
PublisherSpringer Verlag
Pages852-861
Number of pages10
ISBN (Print)3540476938, 9783540476931
Publication statusPublished - 1 Jan 2006
Event5th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2006 - Kobe, Japan
Duration: 6 Nov 20068 Nov 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4259 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2006
Country/TerritoryJapan
CityKobe
Period6/11/068/11/06

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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