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© Anselm Spoerri Lecture 4 Human Visual System –Recap –3D vs 2D Debate –Object Recognition Theories Tufte – Envisioning Information
© Anselm Spoerri Human Visual System – Recap Sensory Representations Effective because well matched to early stages of neural processing Physical World Structured Stages of Visual Processing 1 Rapid Parallel Processing 2Slow Serial Goal-Directed Processing Visual System Detects CHANGES + PATTERNS Luminance Channel More Important than Color Pre-Attentive Features Position Color Simple Shape = orientation, size Motion Depth
© Anselm Spoerri Gestalt Laws – Recap Proximity Similarity Continuity Symmetry Closure Relative Size Figure and Ground
© Anselm Spoerri Space Perception – Recap Depth Cues Shape-from-Shading Shape-from-Contour Shape-from-Texture Shape-from-Motion
© Anselm Spoerri Simple Lighting Model – Recap Diffuse Lambertian SpecularAmbient Shadows Light from above and at infinity Diffuse, Specular and Ambient Reflection Depth Cues
© Anselm Spoerri Depth Cues – Relative Importance – Recap Depth Contrast Depth (meters) Occlusion Relative size Convergence accommodation Binocular disparity Motion parallax Aerial
© Anselm Spoerri 3D vs 2D Debate - Display Abstract Data in 3D? 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
© Anselm Spoerri Relative Position Judgment Fine Judgments - threading a needle –Stereo is important –Shadows –Occlusion Large Scale Judgments –Perspective –Motion parallax –Stereo is not important
© Anselm Spoerri Image + Object Recognition 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
© Anselm Spoerri Template Theories Template with simple morphing operations
© Anselm Spoerri Template Theories – Scale Matters Visual degrees = 4 optimal for object perception
© Anselm Spoerri Geon Theory
© Anselm Spoerri Geon Theory (cont.) 3D Primitives “Geons” Structural skeleton Shape from shading is also primitive
© Anselm Spoerri Canonical Silhouettes
© Anselm Spoerri Recognition – Processing Stages
© Anselm Spoerri Pattern Finding & Recognition – 3D vs 2D 34% memory errors 21% errors 20% memory errors 11.4% errors
© Anselm Spoerri Edward Tufte Books The Visual Display of Quantitative Information Envisioning Information Visual Explanations
© Anselm Spoerri Tufte - Minard's Napoleon's March to Moscow
© Anselm Spoerri Tufte - Escape Flatland: Napoleon's March 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
© Anselm Spoerri Tufte – Challenger Data: Launch? Graph obscures important variables of interest: temperature is shown textually and graphically; degree of damage is not mapped onto a nominal scale
© Anselm Spoerri Tufte – Challenger Data: Launch? Diagrams can lead to great insight, but also to lack of it
© Anselm Spoerri Cause of cholera epidemic in London in 1854? Modified in Visual Explanations by Edward Tufte, Graphics Press, 1997 John Snow’s deduction that a cholera epidemic was caused by a bad water pump
© Anselm Spoerri Tufte’s Measures Maximize data density Data density of graphic = Number entries in data matrix Area of data graphic Measuring Misrepresentation close to 1 Size of effect shown in graphic Size of effect in data Lie factor = Data ink ratio = Data ink Total ink used in graphic Maximize data-ink ratio
© Anselm Spoerri Tufte - Graphical Displays Should 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
© Anselm Spoerri Example Stock market crash?
© Anselm Spoerri Example Show entire scale
© Anselm Spoerri Example Show in context
© Anselm Spoerri Tufte - How to Exaggerate with Graphs “Lie factor” = 2.8
© Anselm Spoerri Tufte - How to Exaggerate with Graphs “Lie factor” = 2.8 Error: Shrinking along both dimensions
© Anselm Spoerri When to use which type? 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
© Anselm Spoerri Tufte - Graph & Chart Tips 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
© Anselm Spoerri Tufte – Hierarchy of Visual Effects
© Anselm Spoerri Tufte – Hierarchy of Visual Effects
© Anselm Spoerri Tufte – Hierarchy of Visual Effects in Maps
© Anselm Spoerri Tufte – Be aware of visual artifacts
© Anselm Spoerri Tufte – Leverage Illusionary Contours
© Anselm Spoerri Tufte – Narratives of Space & Time
© Anselm Spoerri Tufte – Micro / Macro Readings - 2½ Displays Axonometric Projection To Clarify, Add Detail
© Anselm Spoerri Tufte – Micro / Macro Readings - 2½ Displays
© Anselm Spoerri Tufte’s Principles – Summary 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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