... hands, feet, and
facial features.
49
Figure Anatomy
47
Figure Anatomy
Figure 3.6 The female figure has the same muscles as the male figure.
40
Figure Drawing with Virtual Models
arm curves at ... muscles along
the outer ribcage that
attach to the inside of
the scapula. They help
to rotate the scapula,
and thus the arms,
downward. They have
a distinctive rib-like
appearance in a lean
person and ... needs a more
direct joint. The female arm is bet-
ter suited to holding and carrying.
A female can carry an infant longer
without fatigue than a male can,
based on the curvature of the arm.
An interesting...
... to draw lightly than to erase because erasing can dam-
age the paper and ruin the drawing.
138
Figure Drawing with Virtual Models
Light Area
The area that contains the highlight
and the raking ... light
area of an object. Most objects can
be defined as having a light area
and a shadow area. Because the
light area receives the most light,
most of the detail in adrawing is in
this area. Figure ... the shadow area of a
drawing, as shown in Figure 7.14.
Figure 7.15 The cast shadow is the area of shadow
cast from an object onto another surface.
Cast shadow
Figure 7.14 Half the ball is on...
... than before,
again including the occipital, temporal, and the frontal lobes, but
in
particular
bilateral orbital frontal corlex.
What
do
the results
of
Kawabata and Zeki (2004) and Skov
ef
al. ... demonstrated that acllvtly m
the orbital frontal cortex was greater for stimuli classified as beautiful, and the
authors argued that this activation
in
the orbital frontal cortex was due
to
the
reward ... orderly
444
Chapter
Twenty
One
presented at
the
11
'h
annual meeting
of
Human Brain Mapping, Toronto,
ON, Canada.
Vartanian,
0.,
& Gael,
V.
(200 4a) . Emotion pathways
in
the brain mediate
aesthetic preference.
Bulletin...
... boundaries as hidden
variables and include probabilities for let-
ter transitions within segments. The ad-
vantage of this model family is that it can
learn from small datasets and easily gen-
eralises ... MIT
Press, Cambridge, MA, USA.
K. Shalonova, B. Gol
´
enia, and P. A. Flach. 2009. To-
wards learning morphology for under-resourced fu-
sional and agglutinating languages. IEEE Transac-
tions on Audio, ... terms of
training set size. We want to remind the reader that
our two algorithms are aimed at small datasets.
We randomly split each dataset into 10 subsets
where each subset was a test set and the...