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Harnessing
Preattentive
Processes for
Multivariate
Data
Visualization
Christopher
G.
Healey,
Kellogg
S.
Booth, and
James
T.
Enns
Appeared in Graphics Interface '93 (pp. 107-117; Toronto, Ontario)
TR-92-39
ABSTRACT
A new method for designing multivariate data visualization tools is presented.
These tools allow users to perform simple tasks such as estimation, target
detection, and detection of data boundaries rapidly and accurately. Our design
technique is based on principles arising from an area of cognitive psychology
called preattentive processing. Preattentive processing involves visual
features that can be detected by the human visual system without focusing
attention on particular regions in an image. Examples of preattentive features
include colour, orientation, intensity, size, shape, curvature, and line
length. Detection is performed very rapidly by the visual system, almost
certainly using a large degree of parallelism. We studied two known
preattentive features, hue and orientation. The particular question
investigated is whether rapid and accurate estimation is possible using these
preattentive features. Experiments that simulated displays using our
preattentive visualization tool were run. Analysis of the results of the
experiments showed that rapid and accurate estimation is possible with both
hue and orientation. A second question, whether interaction occurs between the
two features, was answered negatively. This suggests that these and perhaps
other preattentive features can be used to create visualization tools which
allow high-speed multivariate data analysis.