• DocumentCode
    2974618
  • Title

    A novel clustering method for Chernoff faces based on V-system

  • Author

    Song, Ruixia ; Zhao, Zhaoxia ; Ou, Meifang

  • Author_Institution
    Coll. of Sci., North China Univ. of Technol., Beijing, China
  • fYear
    2009
  • fDate
    22-24 June 2009
  • Firstpage
    1556
  • Lastpage
    1561
  • Abstract
    The Chernoff faces is a classical method to display multidimensional data graphically in Multivariate Statistics. Based on the V-system, a class of complete orthogonal function system on L2[0,1], a new method to quantify the overall features of Chernoff faces is proposed in this paper. Chernoff faces are firstly transformed into the frequency domain by the V-system, the overall features of Chernoff faces are then obtained. It offers a new programmed clustering method for Chernoff faces. Using it, self-adaptive clustering can carry out by computer. This self-adaptive clustering technique can avoid misjudgment caused by human eyes. Especially, when the number of data sets processing is very large, its advantage is more obvious. The results of the concrete experimental tests indicate that the novel method for clustering Chernoff faces is simple, fast and effective.
  • Keywords
    face recognition; pattern clustering; statistics; Chernoff faces; V-system; complete orthogonal function system; multidimensional data; multivariate statistics; programmed clustering method; self-adaptive clustering; Clustering methods; Eyes; Face detection; Facial features; Humans; Multidimensional systems; Solid modeling; Statistical analysis; Statistics; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation, 2009. ICIA '09. International Conference on
  • Conference_Location
    Zhuhai, Macau
  • Print_ISBN
    978-1-4244-3607-1
  • Electronic_ISBN
    978-1-4244-3608-8
  • Type

    conf

  • DOI
    10.1109/ICINFA.2009.5205165
  • Filename
    5205165