visual perception cecilia r. aragon ieor 170 uc berkeley spring 2006
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Visual Perception
Cecilia R. AragonIEOR 170
UC Berkeley
Spring 2006
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Spring 2006 IEOR 170 2
Acknowledgments
• Thanks to slides and publications by Pat Hanrahan, Christopher Healey, Maneesh Agrawala, and Lawrence Anderson-Huang.
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Spring 2006 IEOR 170 3
Visual perception
• Structure of the Retina• Preattentive Processing • Detection • Estimating Magnitude• Change Blindness• Multiple Attributes• Gestalt
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Spring 2006 IEOR 170 4
Visual perception and psychophysics
Psychophysics is concerned with establishing quantitative relations between physical stimulation and perceptual events.
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Spring 2006 IEOR 170 5
Structure of the Retina
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Spring 2006 IEOR 170 6
Structure of the Retina
• The retina is not a camera!• Network of photo-receptor
cells (rods and cones) andtheir connections
[Anderson-Huang, L. http://www.physics.utoledo.edu/~lsa/
_color/18_retina.htm]
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Spring 2006 IEOR 170 7
Photo-transduction
• When a photon enters a receptor cell (e.g. a rod or cone), it is absorbed by a molecule called 11-cis-retinal and convertedto trans form.
• The different shapecauses it to ultimatelyreduce the electricalconductivity of thephoto-receptor cell.
[Anderson-Huang, L. http://www.physics.utoledo.edu/~lsa/_color/18_retina.htm]
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Spring 2006 IEOR 170 8
Electric currents from photo-receptors
• Photo-receptors generate an electrical current in the dark.
• Light shuts off the current.• Each doubling of light causes
roughly the same reduction of current (3 picoAmps for cones, 6 for rods).
• Rods more sensitive, recover more slowly.
• Cones recover faster, overshoot.
• Geometrical response in scaling laws of perception. [Anderson-Huang, L. http://www.physics
.utoledo.edu/~lsa/_color/18_retina.htm]
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Preattentive Processing
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Spring 2006 IEOR 170 10
How many 5’s?
385720939823728196837293827
382912358383492730122894839
909020102032893759273091428
938309762965817431869241024
[Slide adapted from Joanna McGrenere http://www.cs.ubc.ca/~joanna/ ]
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Spring 2006 IEOR 170 11
How many 5’s?
385720939823728196837293827
382912358383492730122894839
909020102032893759273091428
938309762965817431869241024
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Preattentive Processing
• Certain basic visual properties are detected immediately by low-level visual system
• “Pop-out” vs. serial search• Tasks that can be performed in less than 200 to
250 milliseconds on a complex display• Eye movements take at least 200 msec to
initiate
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Spring 2006 IEOR 170 13
Color (hue) is preattentive
• Detection of red circle in group of blue circles is preattentive
[image from Healey 2005]
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Spring 2006 IEOR 170 14
Form (curvature) is preattentive
• Curved form “pops out” of display
[image from Healey 2005]
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Conjunction of attributes
• Conjunction target generally cannot be detected preattentively (red circle in sea of red square and blue circle distractors)
[image from Healey 2005]
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Spring 2006 IEOR 170 16
Healey appleton preattentive processing
http://www.csc.ncsu.edu/faculty/healey/PP/index.html
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Spring 2006 IEOR 170 17
Preattentive Visual Features
line orientationlengthwidthsizecurvaturenumberterminatorsintersection
closurecolor (hue)intensityflickerdirection of motionstereoscopic depth3D depth cues
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Cockpit dials
• Detection of a slanted line in a sea of vertical lines is preattentive
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Spring 2006 IEOR 170 19
Detection
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Spring 2006 IEOR 170 20
Just-Noticeable Difference
• Which is brighter?
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Spring 2006 IEOR 170 21
Just-Noticeable Difference
• Which is brighter?
(130, 130, 130) (140, 140, 140)
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Spring 2006 IEOR 170 22
Weber’s Law
• In the 1830’s, Weber made measurements of the just-noticeable differences (JNDs) in the perception of weight and other sensations.
• He found that for a range of stimuli, the ratio of the JND ΔS to the initial stimulus S was relatively constant:
ΔS / S = k
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Spring 2006 IEOR 170 23
Weber’s Law
• Ratios more important than magnitude in stimulus detection
• For example: we detect the presence of a change from 100 cm to 101 cm with the same probability as we detect the presence of a change from 1 to 1.01 cm, even though the discrepancy is 1 cm in the first case and only .01 cm in the second.
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Spring 2006 IEOR 170 24
Weber’s Law
• Most continuous variations in magnitude are perceived as discrete steps
• Examples: contour maps, font sizes
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Spring 2006 IEOR 170 25
Estimating Magnitude
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Stevens’ Power Law
• Compare area of circles:
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Stevens’ Power Law
s(x) = axb
s is the sensation
x is the intensity of the attribute
a is a multiplicative constant
b is the power
b > 1: overestimate
b < 1: underestimate[graph from Wilkinson 99]
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Spring 2006 IEOR 170 28
Stevens’ Power Law
[Stevens 1961]
Sensation ExponentBrightness 0.33
Smell 0.55 (Coffee)
Loudness 0.6
Temperature 1.0 (Cold)
Taste 1.3 (Salt)
Heaviness 1.45
Electric Shock 3.5
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Stevens’ Power Law
Experimental results for b:
Length.9 to 1.1
Area .6 to .9
Volume .5 to .8
Heuristic: b ~ 1/sqrt(dimensionality)
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Spring 2006 IEOR 170 30
Stevens’ Power Law
• Apparent magnitude scaling
[Cartography: Thematic Map Design, p. 170, Dent, 96]
S = 0.98A0.87
[J. J. Flannery, The relative effectiveness of some graduated point symbols in the presentation of quantitative data, Canadian Geographer, 8(2), pp. 96-109, 1971] [slide from Pat Hanrahan]
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Relative Magnitude Estimation
Most accurate
Least accurate
Position (common) scale
Position (non-aligned) scale
Length
Slope
Angle
Area
Volume
Color (hue/saturation/value)
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Change Blindness
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Spring 2006 IEOR 170 33
Change Blindness
• An interruption in what is being seen causes us to miss significant changes that occur in the scene during the interruption.
• Demo from Ron Rensink: http://www.psych.ubc.ca/~rensink/flicker/
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Possible Causes of Change Blindness
[Simons, D. J. (2000), Current approaches to change blindness, Visual Cognition, 7, 1-16. ]
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Spring 2006 IEOR 170 35
Multiple Visual Attributes
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Spring 2006 IEOR 170 36
The Game of Set
• Color• Symbol• Number• Shading
A set is 3 cards such that each feature is EITHER the same on each card OR is different on each card.
[Set applet by Adrien Treuille, http://www.cs.washington.edu/homes/treuille/resc/set/]
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Multiple Visual Attributes
• Integral vs. separable Integral dimensions
two or more attributes of an object are perceived holistically (e.g.width and height of rectangle).
Separable dimensions
judged separately, or through analytic processing (e.g.
diameter and color of ball).
• Separable dimensions are orthogonal.• For example, position is highly separable from
color. In contrast, red and green hue perceptions tend to interfere with each other.
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Integral vs. Separable Dimensions
Integral
Separable[Ware 2000]
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Spring 2006 IEOR 170 39
Gestalt
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Spring 2006 IEOR 170 40
Gestalt Principles
• figure/ground• proximity• similarity• symmetry• connectedness• continuity• closure• common fate• transparency
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Examples
Figure/Ground
[http://www.aber.ac.uk/media/Modules/MC10220/visper07.html]
ProximityConnectedness
[from Ware 2004]
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Spring 2006 IEOR 170 42
Conclusion
What is currently known about visual perception can aid the design process.
Understanding low-level mechanisms of the visual processing system and using that knowledge can result in improved displays.