Interaction

1
Interaction

• James Slack
• CPSC 533C
• March 3, 2003

2
Introduction

• Visualization give us interfaces for complex
  computer-based systems
• Interaction reduces cognitive load
• 3 classes of interlocking feedback loops

3
The 3 Feedback Loops

• Visual-Manual Control
• View Refinement and Navigation
• Problem Solving

4
Visual-Manual Control Loop

• Low level interaction
• Visual control of hand position
• Selection of objects on the screen
• Reaction times

5
Choice Reaction Times

• How fast can you choose something?
• Visual signal 130 msec response time
• 700 msec if signals arent expected
• Reaction time proportional to logarithm of the
  number of choices
• Speed-accuracy trade-off

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2D Positioning and Selection

• How fast can you select something (from a
  display, including positioning)?
• Selection time proportional to logarithm of
  distance divided by target object width (Fitts
  law)
• Fitts law can account for other time details
  associated with HCI, like lag

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Visual-Manual Feedback Loop
Human processing
Detect start signal
Judge distance to target
no
Effect hand movement
In target?
yes
Next task
Machine processing
Update display
Measure hand position
Colin Ware, Information Visualization, Chapter
10, page 338
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Skill Learning

• Power law of practice
• Applies to repeated tasks over time
• Experience is a large factor in learning
• Design interfaces should minimize learning new
  tasks
• People can tolerate small changes

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Vigilance

• Principle target detection, sparse targets
• Is this boring? Vigilance is hard
• Vigilance drops greatly over first hour
• Fatigue large negative influence
• Need to focus, no multitasking
• Irrelevant signals reduce vigilance

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Reminder

• Vigilance is hard
• Move visual signal into optimal spatial or
  temporal range helps detection
• Make signals different from noise
• Use of colour, motion, texture to make things
  stand out

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View Refinement Navigation Loop

• Exploration of extended, detailed spaces
• Locomotion
• Viewpoint control
• Map orientation
• Focus, context, scale
• Rapid interaction with data

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Navigation Control Loop
Spatial data model
Cognitive logical and spatial model
Working memory
Visualization of task
Assess progress
Computer databases
Navigation control
Long-term memory
Colin Ware, Information Visualization, Chapter
10, page 343
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Locomotion

• Moving gives dimensionality to space
• Movement should correspond to real life
• Relative movement over time is more important
  than smooth motion
• Low frame rate (2 fps) ok, but lag is issue

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Spatial Navigation Metaphors

• Movement is usually constrained to avoid
  confusion (affordances)
• 4 main classes of movement metaphors
• World-in-hand
• Eyeball-in-hand
• Walking
• Flying

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World-in-hand

• Perception that the environment is moving,
  observer is stationary
• Good for discrete, relatively compact data
  objects
• Bad for long distances, extended terrains
• Used in computer game Black White

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Eyeball-in-hand

• Camera (or eye) is manipulable
• Not the most effective method for viewpoint
  control
• Good ?
• Bad occlusion, hard to get some views, limited
  by users hand positions

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Walking

• Walk around in virtual reality
• Movement in real world constrained (using
  treadmills)
• Good relevant to typical locomotion
• Bad restricted affordances

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Flying

• Navigation as if in an airplane
• Unconstrained movement
• More flexible, usable than other interfaces
• Good relevant to typical locomotion
• Bad given real flight controls, users were
  confused (users had to learn a new skill)

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Reading Maps

• How to get from here to there (Siegel)
• Declare key landmarks
• Develop rules for connecting key landmarks,
  things in between
• Form cognitive spatial map for distances between
  landmarks and relative position

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Landmark rules

• In virtual environments (Vinson),
• Should be enough landmarks visible at all times
• Landmarks should be visually distinct
• Landmarks should be seen at every scale
• Landmarks should be placed in areas of interest

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Map Orientation

• Track-up display orientation
• Up is always the correct way to go
• Right is always right
• North-up display orientation
• North is up, use a compass
• Right becomes left if you go down
• Common frame of reference?

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Visualizing with Maps

• Overview maps are important if the space is large
• User location and direction should be noted
• Key landmark images should be provided
• Instructions other than the map should be
  provided for navigation

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Focus, Context, Scale

• Spatial Scale understanding how changes in scale
  relate
• Structural Scale levels of detail give us an
  appropriate amount of information
• Temporal Scale time compression and data samples
  from many different time ranges

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Distortion

• Hide information that the user doesnt need to
  see by focusing attention where its relevant
• Fish eye, table lens, hyperbolic tree browser are
  good examples of distortion

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Other Navigation Techniques

• Rapid zooming
• Elision techniques
• Hiding information until it is needed, give
  appearance of data being far away, unimportant
• Multiple Windows
• One context each, but each window is linked

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Rapid Interaction with Data

• Interaction should be fluid and dynamic
• Users have to relate cause and effect
• Users may want to customize how visualization
  system displays their data
• Brushing highlighting individual data elements
  interactively (parallel coordinates)

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Problem-Solving Loop

• Using visual representations of data to solve
  problems
• Interactive cycle, use a conceptualization as aid
  to finding solution

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Problem-Solving Loop
Visual-spatial model
Computer based model
Refine and test hypotheses through visualization
Working memory
Visualization of task
Cognitive logical verbal model
Computer databases
Navigation control
Long-term memory network
Colin Ware, Information Visualization, Chapter
10, page 366
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Human Memory

• 3 Types
• Iconic
• Working
• Long-term

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Iconic Memory

• Simple visual buffer holds retinal images
• Will quickly deteriorate if not read out
• The interface between computer display and human
  processing system

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Working Memory

• Limited in capacity
• A cache of sorts for human processor
• Separate subsystems for different tasks
• A general purpose working memory?

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Long-term Memory

• Lifelong memory
• Includes episodic memory, motor skills,
  perceptual skills
• Estimated 109 bits (100 megabytes) stored over
  35 year period
• Ideas, thoughts get lost in concept network
• Misremembering events over time

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Chunks Concepts

• A chunk is a piece of information as a mental
  representation
• Chunks are either specific or general high-level
  concepts are a result of experience
• Concepts formed from hypothesis testing process,
  starting from an initial idea

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Human Computer Similarities

• Both systems share common traits
• Registers / Iconic Memory
• Caches / Working Memory
• Main Memory or storage / Long-term memory
• How is this possible?
• Known to be efficient using computers

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Not Really the Same

• Digital information is much more detailed
• Digital information can be retained indefinitely
• Human visual memory tends to dissipate
• Human storage isnt thought of as atomic elements
  but of chunks and concepts

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Concept Maps, Mind Maps

• Links between concepts form cognitive aid
• The SPIRE system (ThemeScapes)
• Trajectory maps an extrapolation of ideas
• Unified Modeling Language (UML)
• Too cryptic, hard to understand relationships

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Conclusion

• Similar structures exist in humans to interact,
  navigate and problem solve
• Feedback loops are common structures that
  reinforce positive behavior
• Visualization aids problem solving