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Towards Automated Caricature Recognition
(2012-11-22 22:54:20)
A caricature is an
extrapolated version of the original face.
In fact, studies have suggested that people may
be better at recognizing a familiar person through a caricature
portrait than from a veridical portrait.

A major contribution of this
paper is to define a set of categorical, or nominal, facial
attributes. This approach is similar to the attribute and simile
features proposed by Kumar
et al. [18], who demonstrated the benefit of this nominal feature
representation for recognizing face images. While we present a
similar representation, the features proposed here have been
carefully defined by a professional artist with experience in
drawing caricatures.
A caricaturist can be likened
to a “filter” that only retains useful information in a face for
identification. As a filter, the artist uses his talent to analyze
a face, eliminate insignificant facial features, and capture the
identity though exaggeration of the prominent features. Most of the
caricaturists start with the description of the general shape of
the head.
They assemble the eyes, nose, eyebrows, lips, chin and ears with
some exaggerations in geometrically correct locations (always
maintaining the appropriate ratios amongst them);
finally, they include the hair, moustache and beard (depending on
the gender or their presence in the face).
In this study, following the caricaturists
methodology, we define a set of 25 qualitative facial features that
are classified into two levels (see Figure3). The first level
(Level 1) is defined for the general shapes and sizes of the facial
components and the second level (Level 2) is defined for the size
and appearance of facial components, as well as ratios amongst the
locations of different components (e.g. distance of the mouth from
the nose).



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