@CONFERENCE\{IMM2005-04007,
    author       = "J. Fagertun and D. D. Gomez and B. K. Ersb{\o}ll and R. Larsen",
    title        = "A face recognition algorithm based on multiple individual discriminative models",
    year         = "2005",
    month        = "aug",
    keywords     = "Face recognition, Principal Component Analysis, Fisher Linear Discriminant Analysis, Biometrics, Multi-Subspace Method.",
    pages        = "69-75",
    booktitle    = "Dansk Selskab for Genkendelse af M{\o}nstre (Danish Pattern Recognition Society) {DSAGM} 2005",
    volume       = "",
    series       = "{DIKU} Technical report 2005/06",
    editor       = "S{\o}ren I. Olsen",
    publisher    = "{DIKU,} University of Copenhagen",
    organization = "",
    address      = "Universitetsparken {1,} 2100 K{\o}benhavn {\O}",
    url          = "http://www.diku.dk/dsagm2005/",
    abstract     = "Abstract—In this paper, a novel algorithm for facial recognition
is proposed. The technique combines the color texture and
geometrical configuration provided by face images. Landmarks
and pixel intensities are used by Principal Component Analysis
and Fisher Linear Discriminant Analysis to associate a one
dimensional projection to each person belonging to a reference
data set. Each of these projections discriminates the associated
person with respect to all other people in the data set. These
projections combined with a proposed classification algorithm are
able to statistically deciding if a new facial image corresponds to a
person in the database. Each projection is also able to visualizing
the most discriminative facial features of the person associated to
the projection. The performance of the proposed method is tested
in two experiments. Results point out the proposed technique as
an accurate and robust tool for facial identification and unknown
detection.",
    isbn_issn    = "0107-8283"
}