GraphicalVisual Properties

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Graphical/Visual Properties

• CS 7450 - Information Visualization
• January 24, 2002
• John Stasko

2
Agenda

• Two main topics
• Visual perception
• Symbolic display principles
• Probably should be two separate lectures...

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Semiotics

• The study of symbols and how they convey meaning
• Classic book
• J. Bertin, 1983, The Semiology of Graphics

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Related Disciplines

• Psychophysics
• Applying methods of physics to measuring human
  perceptual systems
• How fast must light flicker until we perceive it
  as constant?
• What change in brightness can we perceive?
• Cognitive psychology
• Understanding how people think, here, how it
  relates to perception

5
Perceptual Processing

• Seek to better understand visual perception and
  visual information processing
• Multiple theories or models exist
• Need to understand physiology and cognitive
  psychology

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One (simple) Model

• Two stage process
• Parallel extraction of low-level properties of
  scene
• Sequential goal-directed processing

Stage 1
Stage 2
Early, parallel detection of color,
texture, shape, spatial attributes
Serial processing of object identification
(using memory) and spatial layout, action
Ware 2000
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Stage 1 - Low-level, Parallel

• Neurons in eye brain responsible for different
  kinds of information
• Orientation, color, texture, movement, etc.
• Arrays of neurons work in parallel
• Occurs automatically
• Rapid
• Information is transitory, briefly held in iconic
  store
• Bottom-up data-driven model of processing
• Often called pre-attentive processing

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Stage 2 - Sequential, Goal-Directed

• Splits into subsystems for object recognition and
  for interacting with environment
• Increasing evidence supports independence of
  systems for symbolic object manipulation and for
  locomotion action
• First subsystem then interfaces to verbal
  linguistic portion of brain, second interfaces to
  motor systems that control muscle movements

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Stage 2 Attributes

• Slow serial processing
• Involves working and long-term memory
• More emphasis on arbitrary aspects of symbols
• Top-down processing

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Preattentive Processing

• How does human visual system analyze images?
• Some things seem to be done preattentively,
  without the need for focused attention
• Generally less than 200-250 msecs (eye movements
  take 200 msecs)
• Seems to be done in parallel by low-level vision
  system

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How Many 3s?
1281768756138976546984506985604982826762 980985845
8224509856458945098450980943585 909103020990595959
5772564675050678904567 884578980982167765487636490
8560912949686
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How Many 3s?
1281768756138976546984506985604982826762 980985845
8224509856458945098450980943585 909103020990595959
5772564675050678904567 884578980982167765487636490
8560912949686
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What Kinds of Tasks?

• Target detection
• Is something there?
• Boundary detection
• Can the elements be grouped?
• Counting
• How many elements of a certain type are present?

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Example

• Determine if a red circle is present
• (2 sides of the room)

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Hue
Can be done rapidly (preattentively) by
people Surrounding objects called distractors
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Example

• Determine if a red circle is present

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Shape
Can be done preattentively by people
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Example

• Determine if a red circle is present

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Hue and Shape

• Cannot be done preattentively
• Must perform a sequential search
• Conjuction of features (shape and hue) causes it

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Example

• Is there a boundary in the display?

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Fill and Shape

• Left can be done preattentively since each
  group contains one unique feature
• Right cannot (there is a boundary!) since the
  two features are mixed (fill and shape)

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Example

• Is there a boundary in the display?

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Hue versus Shape
Left Boundary detected preattentively based
on hue regardless of shape Right Cannot do
mixed color shapes preattentively
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Example

• Is there a boundary?

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Hue versus brightness
Left Varying brightness seems to
interfere Right Boundary based on brightness can
be done preattentively
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Example Applet

• Nice on-line tutorial and example applet
• http//www.csc.ncsu.edu/faculty/healey/PP/PP.html
• Chris Healey, NC State

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Preattentive Features

• Certain visual forms lend themselves to
  preattentive processing
• Variety of forms seem to work

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Textons
1. Elongated blobs 2. Terminators 3. Crossings of
lines
All detected early
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3-D Figures
3-D visual reality has an influence
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Emergent Features
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Potential PA Features
hue intensity flicker direction of
motion binocular lustre stereoscopic depth 3-D
depth cues lighting direction
length width size curvature number terminators int
ersection closure
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Key Perceptual Properties

• Brightness
• Color
• Texture
• Shape

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Luminance/Brightness

• Luminance
• Measured amount of light coming from some place
• Brightness
• Perceived amount of light coming from source

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Brightness

• Perceived brightness is non-linear function of
  amount of light emitted by source
• Typically a power function
• S aIn
• S - sensation
• I - intensity
• Very different on screen versus paper

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Grayscale

• Probably not best way to encode data because of
  contrast issues
• Surface orientation and surroundings matter a
  great deal
• Luminance channel of visual system is so
  fundamental to so much of perception
• We can get by without color discrimination, but
  not luminance

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Color

• Sensory response to electromagneticradiation in
  the spectrum betweenwavelengths 0.4 - 0.7
  micrometers

0.5
10-1
10-6
105
108
visible
gamma
ultraviolet
microwave
tv
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Color Models

• HVS model
• Hue - what people think of color
• Value - light/dark, ranges blacklt--gtwhite
• Saturation - intensity, ranges huelt--gtgray

white
Value
Hue
Saturation
black
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Color Categories

• Are there certain canonical colors?
• Post Greene 86had people namedifferent
  colors on amonitor
• Pictured are oneswith gt 75commonality

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Luminance

• Important for fg-bg colors to differ in brightness

Hello, here is some text. Can you read what it
says?
Hello, here is some text. Can you read what it
says?
Hello, here is some text. Can you read what it
says?
Hello, here is some text. Can you read what it
says?
Hello, here is some text. Can you read what it
says?
Hello, here is some text. Can you read what it
says?
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Color for Categories

• Can different colors be used for categories of
  nominal variables?
• Yes
• Wares suggestion 12 colors
• red, green, yellow, blue, black, white, pink,
  cyan, gray, orange, brown, purple

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Color for Sequences
Can you order these (low-gthi)
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Possible Color Sequences
Gray scale
Single sequence part spectral scale
Full spectral scale
Single sequence single hue scale
Double-ended multiple hue scale
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Paper Discuss

• Rogowitz and Treinish
• How NOT to Lie with Visualization
• Discusses different color scales

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Color Purposes

• Call attention to specific data
• Increase appeal, memorability
• Increase number of dimensions for encoding data
• Example, Ware and Beatty 88
• x,y - variables 1 2
• amount of r,g,b - variables 3, 4, 5

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Using Color

• Modesty! Less is more
• Use blue in large regions, not thin lines
• Use red and green in the center of the field of
  view (edges of retina not sensitive to these)
• Use black, white, yellow in periphery
• Use adjacent colors that vary in hue value

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Using Color

• Do not use adjacent colors that vary in amount of
  blue
• Dont use high saturation, spectrally extreme
  colors together (causes after images)
• Use color for grouping and search
• Beware effects from adjacent color regions (my
  old house - example)

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Texture

• Appears to be combination of
• orientation
• scale
• contrast
• Complex attribute to analyze

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Shape, Symbol

• Can you develop a set of unique symbols that can
  be placed on a display and be rapidly perceived
  and differentiated?
• Application for maps, military, etc.
• Want to look at different preattentive aspects

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Glyph Construction

• Suppose that we use two different visual
  properties to encode two different variables in a
  discrete data set
• color, size, shape, lightness
• Will the two different properties interact so
  that they are more/less difficult to untangle?
• Integral - two properties are viewed holistically
• Separable - Judge each dimension independently

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Integral-Separable

• Not one or other, but along an axis

Integral
red-greenred-greenshape heightshapecolordirec
tion motion color color x,y position
yellow-blue black-white shape width size size shap
e shape direction motion size, shape, color
Separable
Ware
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Stage 2

• Missing!
• Object recognition and locomotion/action
• Come back next year )

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Great Book
Information Visualization Perception for
Design Colin Ware Academic Press, 2000
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Basic Symbolic Displays

• Graphs
• Charts
• Maps
• Diagrams

From S. Kosslyn, Understanding chartsand
graphs, Applied CognitivePsychology, 1989.
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1. Graph
Showing the relationships between
variablesvalues in a data table
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Properties

• Graph
• Visual display that illustrates one or more
  relationships among entities
• Shorthand way to present information
• Allows a trend, pattern or comparison to be
  easily comprehended

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Issues

• Critical to remain task-centric
• Why do you need a graph?
• What questions are being answered?
• What data is needed to answer those questions?
• Who is the audience?

money
time
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Graph Components

• Framework
• Measurement types, scale
• Content
• Marks, lines, points
• Labels
• Title, axes, ticks

58
Common Graph Formats
Line graph
Bar graph
Scatter plot
Y-axis is quantitativevariable Compare relative
pointvalues
Two variables, want tosee relationship Is there
a linear, curved orrandom pattern?
Y-axis is quantitativevariable See changes
overconsecutive values
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Graphing Guidelines

• Independent vs. dependent variables
• Put independent on x-axis
• See resultant dependent variables along y-axis
• If there are two independent variables, often
  place them along the 2 axes (you choose which)
  and then the mark may encode the dependent
  variable

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1,2,3 Variables
A B C D E 1 4 1 8 3 5
A B C D E 1 4 1 8 3 5 2 6 3 4 2 1
A B C D E 1 4 1 8 3 5 2 6 3 4 2 1 3 5 7 2 4 3
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2. Chart

• Structure is important, relates entities to each
  other
• Primarily uses lines, enclosure, position to
  link entities

Examples flowchart, family tree, org chart, ...
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3. Map

• Representation of spatial relations
• Locations identified by labels

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Choropleth Map
Areas are filled and colored differently
to indicate some attribute of that region
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Cartography

• Cartographers and map-makers have a wealth of
  knowledge about the design and creation of visual
  information artifacts
• Labeling, color, layout,
• Information visualization researchers should
  learn from this older, existing area

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4. Diagram

• Schematic picture of object or entity
• Parts are symbolic

Examples figures, steps in a manual,
illustrations,...
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Details

• What are the constituent pieces of these four
  symbolic displays?
• What are the building blocks?

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Visual Structures

• Composed of
• Spatial substrate
• Marks
• Graphical properties of marks

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Space

• Visually dominant
• Often put axes on space to assist
• Use techniques of composition, alignment,
  folding, recursion, overloading to 1)
  increase use of space 2) do data encodings

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Marks

• Things that occur in space
• Points
• Lines
• Areas
• Volumes

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Graphical Properties

• Size, shape, color, orientation...

Spatial properties
Object properties
Position Size
Expressing extent
Grayscale
Color Shape Texture
Differentiating marks
Orientation
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Sources Used
Card, Mackinlay, Shneiderman, Information
Vis Healey website and article Marti Hearst SIMS
247 lectures Kosslyn 89 article A. Marcus,
Graphic Design for Electronic Documents and
User Interfaces M. Monmonier, How to Lie with
Maps C. Ware, Information Visualization W.
Cleveland, The Elements of Graphing
Data http//www.csc.ncsu.edu/faculty/healey/PP/PP.
html
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Upcoming

• Tuftes views
• Interaction and dynamic queries