• DocumentCode
    2341093
  • Title

    Face Recognition Using a Multilinear Framework

  • Author

    Wang, Meng

  • Author_Institution
    Dept. of Electron. Eng., Chinese Univ. of Hong Kong, Hong Kong, China
  • fYear
    2010
  • fDate
    23-25 April 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Appearance-based method classifies images by their appearances, using statistical knowledge learned from training data. This paper presents a framework of multilinear algebra-based face recognition, which proposes the use of tensor projector. We will discuss the choice of distance function, which is not usually paid attention to in most research on this area. In fact, a properly chosen distance function is nontrivial to the recognition rate, even for the linear Tensorface method. This implies that if we apply a more advanced method such as ICA, an even better performance can be achieved. At the end of this paper, we present our experiment result based on the framework, which was performed on the Freiburg face database.
  • Keywords
    face recognition; independent component analysis; linear algebra; Freiburg face database; appearance-based method; distance function; face recognition; independent component analysis; multilinear algebra; statistical knowledge; tensor projector; Data engineering; Face detection; Face recognition; Image recognition; Lighting; Matrix decomposition; Principal component analysis; Random variables; Tensile stress; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Computer Science (ICBECS), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5315-3
  • Type

    conf

  • DOI
    10.1109/ICBECS.2010.5462474
  • Filename
    5462474