• DocumentCode
    1543411
  • Title

    Dual eigenspace method for human face recognition

  • Author

    Peng, H. ; Zhang, D.

  • Author_Institution
    Dept. of Comput. Sci., City Univ. of Hong Kong, Kowloon, Hong Kong
  • Volume
    33
  • Issue
    4
  • fYear
    1997
  • fDate
    2/13/1997 12:00:00 AM
  • Firstpage
    283
  • Lastpage
    284
  • Abstract
    The authors present an effective scheme called the dual eigenspace method (DEM) for automated face recognition. Based on the K-L transform, the dual eigenspaces are constructed by extracting algebraic features of training samples and applied to face identification with a two-layer minimum distance classifier. Experimental results show that DEM is significantly better than the traditional eigenface method (TEM)
  • Keywords
    eigenvalues and eigenfunctions; face recognition; feature extraction; identification; object recognition; K-L transform; algebraic features extraction; automated face recognition; dual eigenspace method; face identification; human face recognition; training samples; two-layer minimum distance classifier;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:19970203
  • Filename
    583476
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1543411