LPP solution schemes for use with face recognition

Yong Xu, Aini Zhong, Jian Yang, Dapeng Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

173 Citations (Scopus)

Abstract

Locality preserving projection (LPP) is a manifold learning method widely used in pattern recognition and computer vision. The face recognition application of LPP is known to suffer from a number of problems including the small sample size (SSS) problem, the fact that it might produce statistically identical transform results for neighboring samples, and that its classification performance seems to be heavily influenced by its parameters. In this paper, we propose three novel solution schemes for LPP. Experimental results also show that the proposed LPP solution scheme is able to classify much more accurately than conventional LPP and to obtain a classification performance that is only little influenced by the definition of neighbor samples.
Original languageEnglish
Pages (from-to)4165-4176
Number of pages12
JournalPattern Recognition
Volume43
Issue number12
DOIs
Publication statusPublished - 1 Dec 2010

Keywords

  • Face recognition
  • Feature extraction
  • Locality preserving projection
  • Small sample size problems

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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