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.
Original language | English |
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Title of host publication | Dansk Selskab for Genkendelse af Mønstre (Danish Pattern Recognition Society) DSAGM 2005 |
Publisher | Department of Computer Science, University of Copenhagen (DIKU) |
Publication date | 2005 |
Pages | 69-75 |
Publication status | Published - 2005 |
Event | Dansk Selskab for Genkendelse af Mønstre (Danish Pattern Recognition Society) DSAGM 2005 - Duration: 1 Jan 2005 → … |
Conference
Conference | Dansk Selskab for Genkendelse af Mønstre (Danish Pattern Recognition Society) DSAGM 2005 |
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Period | 01/01/2005 → … |