• DocumentCode
    3100284
  • Title

    The MCF Model: Utilizing Multiple Colors for Face Recognition

  • Author

    Li, Billy ; An, Senjian ; Liu, Wanquan ; Krishna, Aneesh

  • Author_Institution
    Dept. of Comput., Curtin Univ., Perth, WA, USA
  • fYear
    2011
  • fDate
    12-15 Aug. 2011
  • Firstpage
    1029
  • Lastpage
    1034
  • Abstract
    Finding a good color space is one of the main research goals for color face recognition. Existing research shows that RGB can improve over gray-scale, while some other color spaces (YQCr for instance) can improve over RGB. However, all developed color models consist of only three color components transformed linearly from RGB. Since three colors may not capture sufficient information for solving complex face recognition problems and non-linear transformed colors usually encode very different information, this paper investigates the feasibility and effectiveness of using more than three colors including some non-linear color spaces. We propose a novel color combination algorithm namely the Multiple Color Fusion (MCF) model to utilize multiple colors. Experiment 4 on FRGC2 is conducted to demonstrate the effectiveness of MCF. In particular, MCF outperforms any existing three-color based methods by at least 3% and improves over RGB by 8%.
  • Keywords
    face recognition; image colour analysis; nonlinear programming; FRGC2; MCF model; RGB; YQCr; color combination algorithm; color components; color face recognition; complex face recognition problems; gray-scale; multiple color fusion model; multiple colors; nonlinear color spaces; nonlinear transformed colors; three-color based methods; Computational modeling; Face; Face recognition; Feature extraction; Fuses; Image color analysis; Training; Color Face Recognition; FRGC; Multiple Color Fusion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Graphics (ICIG), 2011 Sixth International Conference on
  • Conference_Location
    Hefei, Anhui
  • Print_ISBN
    978-1-4577-1560-0
  • Electronic_ISBN
    978-0-7695-4541-7
  • Type

    conf

  • DOI
    10.1109/ICIG.2011.109
  • Filename
    6005987