@InProceedings{ThomazAmGiKiSaGi:2009:MuDiAn,
               author = "Thomaz, Carlos Eduardo and Amaral, Vagner and Giraldi, Gilson 
                         Antonio and Kitani, Edson Caoru and Sato, Joao Ricardo and 
                         Gillies, Duncan Fyfe",
          affiliation = "{Centro Universitario da FEI (FEI)} and {Centro Universitario da 
                         FEI (FEI)} and {Laboratorio Nacional de Computacao Cientifica 
                         (LNCC)} and {Universidade de Sao Paulo (USP)} and {Universidade 
                         Federal do ABC (UFABC)} and {Imperial College London}",
                title = "A multi-linear discriminant analysis of 2D frontal face images",
            booktitle = "Proceedings...",
                 year = "2009",
               editor = "Nonato, Luis Gustavo and Scharcanski, Jacob",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 22. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Linear Discriminant Analysis, Hyperplane Navigation, Face 
                         Images.",
             abstract = "We have designed and implemented a multi-linear discriminant 
                         method of constructing and quantifying statistically significant 
                         changes on human identity photographs. The method is based on a 
                         general multivariate two-stage linear framework that addresses the 
                         small sample size problem in high-dimensional spaces. Starting 
                         with a 2D face data set of well framed images, we determine a most 
                         characteristic direction of change by organizing the data 
                         according to the features of interest. Our goal here is to use all 
                         the facial image features simultaneously rather than separate 
                         models for texture and shape information. Our experiments show 
                         that the method does produce plausible unseen views for gender, 
                         facial expression and ageing changes. We believe that this method 
                         could be widely applied for normalization in face recognition and 
                         in identifying subjects after a lapse of time.",
  conference-location = "Rio de Janeiro, RJ, Brazil",
      conference-year = "11-14 Oct. 2009",
                  doi = "10.1109/SIBGRAPI.2009.15",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2009.15",
             language = "en",
                  ibi = "8JMKD3MGPBW4/362SDBB",
                  url = "http://urlib.net/ibi/8JMKD3MGPBW4/362SDBB",
           targetfile = "57160_finalversion.pdf",
        urlaccessdate = "2024, May 02"
}