Chernoff faces have been proposed as a tool for
scientific and information visualization.
However, the effectiveness of this form of
visualization is still open to speculation.
Chernoff faces, it is suggested, make use of
humans' apparently inherent ability to recognize
faces and small changes in facial characteristics.
Limited research has been conducted to assess
how well Chernoff faces make use of this ability.
So far, it is still unclear how humans recognize
faces and whether or not a specific set of rules
governs the process. A particular area of interest
is whether or not certain features are pre-attentive. Furthermore, what effect a certain
number of distracters (i.e. more faces) have on
the attentiveness of various features is also of
concern. This information could be used to
maximize the effectiveness of Chernoff faces by
providing an indication of which applications
would be best served by the use of Chernoff
faces. In order to address this issue, we have
conducted a user study, which tested the
effectiveness and pre-attentiveness of several
features of Chernoff faces. Our user study
indicated that the perception of eye size, a
specific face, eyebrow slant, and the combination
eyebrow slant with eye size is a serial process
(not pre-attentive). Our study also indicated that
for longer viewing times (two seconds), eye size
and eyebrow slant were the most accurate
features. These initial results indicate that
Chernoff faces may not have a significant
advantage over other iconic visualization
techniques for multidimensional information
visualization.