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- Information Visualization Intro – Recap
- Foundation in Human Visual Perception
- Sensory vs. Cultural
- Attention – Searchlight Model
- Stages of Visual Processing
- Luminance & Color Channels
- Pre-Attentive Processing
- Mapping Data to Display Variables
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- Use human perceptual capabilities
to gain insights into large data sets
that are difficult to extract
using standard query languages
- Support Exploration
- Look for structure, patterns, trends, anomalies, relationships
- Provide a qualitative overview of large, complex data sets
- Assist in identifying region(s) of interest and appropriate parameters
for more focussed quantitative analysis
- Abstract and Large Data Sets
- Symbolic
- Tabular
- Networked
- Hierarchical
- Textual information
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- Scientific Visualization
- Show abstractions, but based on physical space
- Information Visualization
- Information does not have any obvious spatial mapping
- Fundamental Problem
- How to map non–spatial abstractions
into effective visual form?
- Goal
- Use of computer-supported, interactive, visual
representations of abstract data to amplify cognition
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- Copy the following URL into Browser window:
- http://www.scils.rutgers.edu/~aspoerri/Teaching/InfoVisResources/student_videos/
- and Right click on hyperlink for the name below
and use “Save As …” download avi file to computer
- Phil Bright
- http://www.scils.rutgers.edu/~aspoerri/Teaching/InfoVisResources/student_videos/bright.avi
- Carlos Carrero
- http://www.scils.rutgers.edu/~aspoerri/Teaching/InfoVisResources/student_videos/carrero.avi
- Daveia Thomas
- http://www.scils.rutgers.edu/~aspoerri/Teaching/InfoVisResources/student_videos/thomas.avi
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- 1 Foundation in Human Visual
Perception
- How it relates to creating effective information visualizations
- 2 Understand Key Design
Principles
for Creating Information Visualizations
- 3 Study Major Information
Visualization Tools
- 4 Evaluate Information
Visualizations Tools
- 5 Design New, Innovative
Visualizations
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- Sensory vs. Cultural
- Attention – Searchlight Model
- Stages of Visual Processing
- Luminance & Color Channels
- Pre-Attentive Processing
- Mapping Data to Display Variables
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- Visualization = Learned Language ?
- Meaning of Symbol = Created by Convention
- If true, choice of visual representation arbitrary
- Semiotics = Study of Symbols and how they convey Meaning
- Choice of Visual Representation Matters
- Outlines
- Object outline and object itself excite similar neural processes
- Visual cortex designed to detect continuous contours
- Similar perceptual illusions / blindness in humans and animals
- Not all diagrammatic notations are equal
- Most visualizations are Hybrids
- Learned conventions and hard-wired processing
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- Well-Defined Surfaces
Objects have mostly smooth surfaces
- Temporal Persistence
Objects don’t randomly appear/vanish
- Light travels in Straight Lines
reflects off surfaces in certain ways
- Law of Gravity
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- Sensory Representations
- Tap into Perceptual Power of Brain Without Learning
- Sensory Representations Effective
- because well matched to early stages of neural processing
- Understanding without training
- Perceptual Illusions Persist
Mueller-Lyon Illusion (off by 25-30%)
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- Searchlight Size varies with
- Data density
- Stress level
- Attention Operators work within searchlight beam
- Attention = Tunable Filter
- Eye movements 3/sec – series of saccades
- Popout Effects (general attention)
- Segmentation Effects (dividing up the visual field)
- č Guide Attention
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- 1 Rapid Parallel Processing
- Feature Extraction: orientation, color, texture, motion
- Transitory: briefly held in an iconic store
- Bottom-up, data-driven processing
- 2 Serial Goal-Directed Processing
- Object recognition: visual attention & memory important.
- Slow and serial processing
- Uses both short-term memory and long-term memory
- More emphasis on arbitrary aspects of symbols
- Different pathways for object recognition & visually guided motion
- Top-down processing
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- Extracts Surface Information
- Discounts Illumination Level
- Discounts Color of Illumination
- Mechanisms
- 1 Adaptation
- 2 Simultaneous Contrast
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- Luminance = physical measure
- Brightness = perceived amount of light
- Eye sensitive over 9 orders or magnitude
- 5 orders of magnitude (room – sunlight)
- Receptors bleach and less sensitive with more light
- Takes up to half an hour to recover sensitivity
- Eye is NOT a light meter
- Designed to detect CHANGES
- Not good for detecting Absolute Values
- Extremely sensitive to Differences & Changes
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- Color Perception is Relative
- Sensitive to Small Differences
- hence need sixteen million colors
- Not Sensitive to Absolute Values
- hence we can only use < 10 colors for coding
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- Luminance Channel
- Detail
- Form
- Shading
- Motion
- Stereo
- Chromatic Channels
- Surfaces of Things
- Labels
- Categories (about 6-10)
- Red, green, yellow
and blue are special (unique hues)
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- Use Luminance for Detail, Shape and Form
- Use Color for Categorization - few colors
- Minimize Contrast Effects
- Strong colors for small areas
Contrast in luminance with background
- Subtle colors for large areas
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- Some Visual Properties Processed Pre-Attentively
- No need to focus attention
- Pre-Attentive Properties Important
for Design of Visualizations
- Can be perceived immediately
- Can mislead viewer
- < 200 - 250ms
- Eye movements = at least 200ms
- Some processing can be done very quickly
- č Implies low-level
processing in parallel
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- Number of irrelevant items varies
- Pre-attentive 10 msec per item or better.
- Decision = Fixed Time
regardless of the number of distractors
č Preattentive
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- Must Stand Out in Simple Dimension
- Color
- Simple Shape = orientation, size
- Motion
- Depth
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- Form orientation/size
- Color
- Simple Motion/Blinking
- Spatial, Stereo Depth, Shading, Position
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- Pre-Attentive Demo by Christopher Healey
- Target = Red Circle
- Distractors
- blue circles (colour search)
- red squares (shape search)
- blue circles and red squares (conjunction search)
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- Position + Color
- Position + Shape
- Stereo + Color
- Color + Motion
- č Spatial location + some
aspect of form
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- Design Symbols
- Based on simple visual attributes
- Make symbols distinct
- Support Rapid Visual Search (10 msec/item)
- Use different channels for different types of information
- Do not use large areas of strong color
- Faces, etc are not pre-attentive
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- Position (2)
- Orientation (1)
- Size (spatial frequency)
- Motion (2)++
- Blinking?
- Color (3)
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- QUANTITATIVE
- Position
- Length
- Angle
- Slope
- Area
- Volume
- Density
- Color Saturation
- Color Hue
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