%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi@80/2009/09.09.21.33
%2 sid.inpe.br/sibgrapi@80/2009/09.09.21.33.10
%@doi 10.1109/SIBGRAPI.2009.15
%T A multi-linear discriminant analysis of 2D frontal face images
%D 2009
%A Thomaz, Carlos Eduardo,
%A Amaral, Vagner,
%A Giraldi, Gilson Antonio,
%A Kitani, Edson Caoru,
%A Sato, Joao Ricardo,
%A Gillies, Duncan Fyfe,
%@affiliation Centro Universitario da FEI (FEI)
%@affiliation Centro Universitario da FEI (FEI)
%@affiliation Laboratorio Nacional de Computacao Cientifica (LNCC)
%@affiliation Universidade de Sao Paulo (USP)
%@affiliation Universidade Federal do ABC (UFABC)
%@affiliation Imperial College London
%E Nonato, Luis Gustavo,
%E Scharcanski, Jacob,
%B Brazilian Symposium on Computer Graphics and Image Processing, 22 (SIBGRAPI)
%C Rio de Janeiro, RJ, Brazil
%8 11-14 Oct. 2009
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K Linear Discriminant Analysis, Hyperplane Navigation, Face Images.
%X 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.
%@language en
%3 57160_finalversion.pdf