Visual Distinctness
What is easy to find
How to represent quantitity
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Lessons from low-level vision
Applications in Highlighting
Icon (symbol) design - Nominal
Glyph design – representing quantity
Spotfire product
Visual symbols
Architecture for visual thinking
Primitives of Perception (the
graphemes).
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The whole visual field is processed in
parallel
This machinery tells us what kinds of
information are easily distinguished
Popout effects (general attention)
Segmentation effects (dividing up the
visual field)
Channel theory
Segmentation by Primitive
Features
Orientation and Size
(Gabor primitives)
Image segmentation based on
texture
Vertical fat G abor
filters respond m ost
strongly
H orizontal skinny
G abor filters respond
m ost strongly
R esulting
S egm entation
Textures
for Maps
What is easy to find?
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A priori salience
Top down salience
Knowledge
Pre-Attentive Processing
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Color is Pre-Attentive (Pops out)
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Generic Pre-Attentive Experiment
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Number of irrelevant
items varies
Pre-attentive 10 msec
per item or better.
Triesman, A., and Gormican, S.
Feature analysis in early vision:
Evidence from search
asymmetries. Psychological
Review, 95(1) 15-48.
Color
Orientation
Motion
Size
Simple shading
Conjunction (does not pop out)
Semantic Depth of Field
Compound features (do not pop
out)
Surrounded colors do not pop out
Laws of pre attentive display
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Must stand out on some simple dimension
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color,
simple shape = orientation, size
motion,
depth
Lessons for highlighting – one of each
Asymmetries
Lessons: Highlighting how to make
information available to attention
Using color
Using underlining
A flying box leads attention
Blinking momentarily attracts attention
Motion elicits an orienting response
More on Conjunction (no pop)
Redundant coding
Pre-attentive conjunction
Conjunctions of motion and
shape do pop out. (color also?)
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McLeod, P., Driver, J. and Crisp, J. (1988)
Visual search for a conjunction of movement
and form is parallel. Nature 332, 154-155.
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Driver, J., MacLeod, P. and Dienes, Z. (1992)
Motion coherence and conjunction search:
Implications for guided search theory.
Perception and Psychophysics. 51, 1, 79-85.
MEGraph: Experimental system
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Allows for various topological range
highlighting methods
MEGraph
Goal
from 30 to 2000 nodes
Pre-Attentive Channels
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Form (orientation/size)
Color
Simple motion/blinking
Addition/numerosity (up to 3)
Spatial, stereo depth, shading, position
Pre-Attentive Conjunctions
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Stereo and color
Color and motion
Color and position
Shape and position
In general: spatial location and some
aspect of form
Pre-Attentive Lessons
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Rapid visual search (10 msec/item)
Easy to attend to
Makes symbols distinct
Based on simple visual attributes
Faces, etc are not pre-attentive
Designing symbols
Perceptual Channels
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Color (3)
Shape (size, orient)
Motion (2?)
Texture (2++)
Position (x,y)
Spatial Channels
Like interferes with like
Distortions: Size contrast effect
Orient contrast
Size contrast effects can cause errors in
information display
Chris Weigle: orientation
channels for info display
Mapping data to display variables
Data glyphs
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Position (2)
Orientation (1)
Size (spatial frequency)
Motion (2)++
Blinking?
Star glyph
Color (3)
Method
Note we have the
problem of heterogeneity
– There is no good
solution
Starplot glyph
Spotfire product
Integral and Separable dimension
(Garner)
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Can we read display attributes
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Independently
Holistically
Speeded classification task. Sort into two
piles on one dimension or another
Integral
red-green
yellow-blue
black-white
red-green
x-size
y-size
Color
orientation
Motion
Color
Separable
Lessons for Information Display
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Orthogonality - use a
different channel for a
different type of
information
If you need this use
separable challenge
If you need to highlight
by two properties use
separable dimensions.
The programmable filter
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We can only look for patterns of simple features
Conjunctions of shape, color cannot be
programmed for parallel search of field
Conjunctions of depth/motion and color/shape
can be
Integral dimensions tend to be seen holistically
cannot be separated
Separable dimensions tend to be seen
separately
Searchlight Model of Attention
U s eful Visua l
F ield of View
Visual
S earc h or
M onitori ng
S trat egy
Eye
M ovem e nt
C ontrol
Searchlight Properties
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Size varies with data density
Size varies with stress level
Attention operators work within the
searchlight beam
Attention is a tunable filter
Eye movements 3/sec – A series of
saccades