Two-dimensional Laplacianfaces method for face recognition

Ben Niu, Qiang Yang, Chi Keung Simon Shiu, Sankar Kumar Pal

Research output: Journal article publicationJournal articleAcademic researchpeer-review

39 Citations (Scopus)


In this paper we propose a two-dimensional (2D) Laplacianfaces method for face recognition. The new algorithm is developed based on two techniques, i.e., locality preserved embedding and image based projection. The 2D Laplacianfaces method is not only computationally more efficient but also more accurate than the one-dimensional (1D) Laplacianfaces method in extracting the facial features for human face authentication. Extensive experiments are performed to test and evaluate the new algorithm using the FERET and the AR face databases. The experimental results indicate that the 2D Laplacianfaces method significantly outperforms the existing 2D Eigenfaces, the 2D Fisherfaces and the 1D Laplacianfaces methods under various experimental conditions.
Original languageEnglish
Pages (from-to)3237-3243
Number of pages7
JournalPattern Recognition
Issue number10
Publication statusPublished - 1 Oct 2008


  • Eigenfaces
  • Feature extraction
  • Fisherfaces
  • Image based projection
  • Two-dimensional Laplacianfaces

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering


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