feature level processing lessons from low-level vision applications in highlighting icon (symbol)...
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Feature Level Processing
Lessons from low-level vision Applications in Highlighting Icon (symbol) design Glyph design
Spotfire product
Visual symbols
Architecture for visual thinking
Primitives of Perception (the phonemes).
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)
Segmentation by Primitive Features
Livingston and Hubel
Neural Architecture
a
formcolor
12&34A4B
56
4C
Visual Area 1 (Primary Visual Cortex)
formstereo
stereo
stereo
form
form
MT movement/stereo
Visual Area 2movement
color
color
colorform
form
movement
Orientation and Size(Gabor primitives)
Image segmentation based on texture
ResultingSegmentation
Vertical fat Gaborfilters respond moststrongly
Horizontal skinnyGabor filters respondmost strongly
Vector fields like using gabors
Pre-Attentive Processing
a
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Color is Pre-Attentive (Pops out)
aa
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Generic Pre-Attentive Experiment
a
3 6 12
Number of distractors
500
700
900 Number of irrelevant items varies
Pre-attentive 10 msec per item or better.
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
Must stand out on some simple dimension color, simple shape = orientation, size motion, depth
Lessons for highlighting – one of each
Blinking momentarily attracts attention
Lessons: Highlighting how to make information available to attention
A flying box leads attention
Using colorUsing underlining
Blinking momentarily attracts attention
Motion elicits an orienting response
More Pre-Attentive
Conjunction (does not pop out)
Pre-attentive conjunction
Conjunctions of motion and shape do pop out. (color also?)
McLeod, P., Driver, J. and Crisp, J. (1988) Visual search for a conjunction of movement and form is parallel. Nature 332, 154-155.
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
Allows for various topological range highlighting methods
Goal from 30 to 2000 nodes
MEGraph
Pre-Attentive Channels
Form (orientation/size) Color Simple motion/blinking Addition/numerosity (up to 3) Spatial, stereo depth, shading, position
Pre-Attentive Conjunctions
Stereo and color Color and motion Color and position Shape and position
In general: spatial location and some aspect of form
Pre-Attentive Lessons
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
Color (3) Shape (size, orient) Motion (2?) Texture (2++) Position (x,y)
Spatial Channels
Like interferes with like
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 variablesData glyphs
Position (2) Orientation (1) Size (spatial frequency) Motion (2)++ Blinking? Color (3)
Note we have the problem of heterogeneity – There is no good solution
Star glyphMethod
Starplot glyph
Spotfire product
Integral and Separable dimension (Garner)
Can we read display attributes Independently Holistically
Speeded classification task. Sort into two piles on one dimension or another
Separable
Integral
Motion Color
red-green yellow-blue
black-white red-green
x-size y-size
Color orientation
Lessons for Information Display
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
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
a
VisualSearch orMonitoringStrategy
EyeMovementControl
Useful VisualField of View
Searchlight Properties
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