Visual thinking colin_ware_lectures_2013_1_introduction
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Visual Queries: The foundation of visual thinking Colin Ware Data Visualization Research Lab University of New Hampshire Designing with cyborgs in mind
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Transcript of Visual thinking colin_ware_lectures_2013_1_introduction
Visual Queries:The foundation of visual thinking
Colin WareData Visualization Research Lab
University of New Hampshire
Designing with cyborgs in mind
Change Blindness
Simons and Levin
Vogel Woodman and Luck
Capacity of visual working memory 3 simple shapes
Sequential comparison task
Central Problem: How do we perceivethe world in all its rich detail?
Only detail in fovea Only a small amount of Information in
visual working memory.
Solution “The world is its own memory” O’Regan Task-related active vision “What you see is what you need” Treish et al. (2003)
Seeing is a process that helps us solve problems
Visualizations are much better databases than what we have in our heads
Architecture for visual thinking
Stage 2 Pattern perception
Visual queries are executed by finding patterns in displays
Attentional DemandsTune the pattern finding processes
Top down meets bottom up
Visual search
a
VisualSearch orMonitoringStrategy
EyeMovementControl
Useful VisualField of View
Eye movements
Two or three a second Preserves Context
We seek patterns
ME GraphConstellation
Why visualize?
Human Memory: 100 meg (Landauer)
= 108 (not unique) World information: 1 exabyte/year = 1018 (unique) = 108 bytes new information per person per year
Conclusion: we are cognitive cyborgs – our memories are not in our heads.
Why do we care about perception?
It is about what makes information display effective.
Can there be a science of visualization? Evaluation
Visualizations
Maps Route Flow Thematic (geology, vegetation, etc)
Multi-dimensional Discrete Multi-dimensional continuous Graphs
Social Networks Flow
Narrative – explaining data Animations, assembly diagrams
Other thinking tools Calendars, Planners, search engines, News pages, Design tools
Understanding surface shape
Victoria Interrante
Linked Linked WindowsWindows
Tide Tide AwareAware
Show Show GeoNavGeoNav
GeoZui4D
Flow visualization How do we optimally display vector fields?
Length - 420 ft 16,000 Tons Beam – 82 ft 30,000 HP Draft – 29 ft Diesel Elec AC/AC
Fuel – 1,165,000 gal Top Speed – 17kts Ice Breaking – 4.5 ft @ 3 kts
CAVE
Head tracking – stereo Resolution problems Light scattering problems Vergence focus problem for near object Occlusion problems for near objects
Capacity of visual working memory (Vogal, Woodman, Luck, 2001) Task – change detection Can see 3.3 objects Each object can be complex
1 second
Just enough, just in time
Dual Processing
DisplayFeatures
Proto-objects andPatterns
VisualWorkingMemory
GIST
VisualQuery
VerbalWorkingMemory
Egocentric object andPattern map
OBJECTFILES“Nexus”
Dog
Attention and Patterns
