• DocumentCode
    3263874
  • Title

    A New Incremental Face Recognition System

  • Author

    Ghassabeh, Youness Aliyari ; Ghavami, Abouzar ; Moghaddam, Hamid Abrishami

  • Author_Institution
    K. N. Toosi Univ. of Technol., Tehran
  • fYear
    2007
  • fDate
    6-8 Sept. 2007
  • Firstpage
    335
  • Lastpage
    340
  • Abstract
    In this paper, we present new adaptive linear discriminant analysis (LDA) algorithm and apply them for adaptive facial feature extraction. Adaptive nature of the proposed algorithm is advantageous for real world applications in which one confronts with a sequence of data such as online face recognition and mobile robotics. Application of the new algorithm on feature extraction from facial image sequences is given in three steps: (i) adaptive image preprocessing, (ii) adaptive dimension reduction and (iii) adaptive LDA feature estimation. Steps 1 and 2 are done simultaneously and outputs of stage 2 are used as a sequence of inputs for stage 3. The proposed system was tested on Yale and PIE face databases. Experimental results on these databases demonstrated the effectiveness of the proposed system for adaptive estimation of feature space for online face recognition.
  • Keywords
    face recognition; feature extraction; adaptive LDA feature estimation; adaptive dimension reduction; adaptive facial feature extraction; adaptive image preprocessing; adaptive linear discriminant analysis; incremental face recognition system; mobile robotics; Data mining; Face recognition; Facial features; Feature extraction; Image databases; Image sequences; Linear discriminant analysis; Mobile robots; Spatial databases; System testing; Adaptive dimension reduction; Adaptive linear discriminant analysis; Feature extraction; Incremental face recognition system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2007. IDAACS 2007. 4th IEEE Workshop on
  • Conference_Location
    Dortmund
  • Print_ISBN
    978-1-4244-1347-8
  • Electronic_ISBN
    978-1-4244-1348-5
  • Type

    conf

  • DOI
    10.1109/IDAACS.2007.4488435
  • Filename
    4488435