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- Human Visual System
- Recap
- 3D vs 2D Debate
- Object Recognition Theories
- Tufte – Envisioning Information
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2
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- Sensory Representations Effective
because well matched to early stages of neural processing
- Physical World Structured
- Stages of Visual Processing
- 1 Rapid Parallel Processing
- Slow Serial Goal-Directed Processing
- Visual System Detects CHANGES + PATTERNS
- Luminance Channel More Important than Color
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3
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4
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- Depth Cues
- Shape-from-Shading
- Shape-from-Contour
- Shape-from-Texture
- Shape-from-Motion
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5
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6
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7
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- Depth Cue Theory
- Depth cues are environmental information about space
- Occlusion most important Depth Cue
- Perspective may not add anything by itself
- Stereo important for Close Interaction
- Motion important for 3D layout
- Surface Perception
- Shape-from-Shading
- Shape-from-Texture
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8
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- Fine Judgments - threading a needle
- Stereo is important
- Shadows
- Occlusion
- Large Scale Judgments
- Perspective
- Motion parallax
- Stereo is not important
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- Properties of Image Recognition
- Remarkable image recognition memory
- Up to 5 images per second
- Applications in image searching interfaces
- Easier to Recognize than to Recall
- Image Based Theories
- Template theories based on 2D image processing
- Structural 3D Theories
- Extract structure of a scene in terms of 3D primitives
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11
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12
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13
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14
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15
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16
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17
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- Books
- The Visual Display of Quantitative Information
- Envisioning Information
- Visual Explanations
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19
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- Enforce Visual Comparisons
- Width of tan and black lines gives you an immediate comparison of the
size of Napoleon's army at different times during march.
- Show Causality
- Map shows temperature records and some geographic locations that shows
that weather and terrain defeated Napoleon as much as his opponents.
- Show Multivariate data
- Napoleon's March shows six: army size, location (in 2 dimensions),
direction, time, and temperature.
- Use Direct Labeling
Integrate words, numbers & images
- Don't make user work to learn your "system.”
- Legends or keys usually force the reader to learn a system instead of
studying the information they need.
- Design Content-Driven
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20
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21
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- Diagrams can lead to great insight, but also to lack of it
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24
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- Show Data
- Focus on Content instead of graphic production
- Avoid Distorting what Data has to say
- Make Large Data Sets Coherent
- Encourage Eye to Compare Different Pieces of Data
- Reveal Data at several Levels of Detail
- Closely integrate Statistical and Verbal Descriptions
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30
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- Line Graph
- x-axis requires quantitative variable
- Variables have contiguous values
- familiar/conventional ordering among ordinals
- Bar Graph
- comparison of relative point values
- Scatter Plot
- convey overall impression of relationship
between two variables
- Pie Chart
- Emphasizing differences in proportion
among a few numbers
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- Avoid Separate Legends and Keys
- Make Grids, labeling, etc., Very Faint so that they recede into
background
- Graphical Integrity
- Where’s baseline?
- What’s scale?
- What’s context?
- Watch Size Coding: Height/width vs. area vs. volume
- Using Color Effectively
- To label
- To measure
- To represent or imitate reality
- To enliven or decorate
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35
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37
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38
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39
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40
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- Good Information Design = Clear Thinking Made Visible
- Greatest number of Ideas
in Shortest Time
with Least Ink in the Smallest Space
- Principles
- Enforce Visual Comparisons
- Show Comparisons Adjacent in Space
- Show Causality
- Show Multivariate Data
- Use Direct Labeling
- Use Small Multiples
- Avoid “Chart Junk”: Not needed extras to be cute
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