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Visual Perception

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Title: Visual Perception


1
Visual Perception
  • Cecilia R. Aragon
  • IEOR 170
  • UC Berkeley
  • Spring 2006

2
Acknowledgments
  • Thanks to slides and publications by Pat
    Hanrahan, Christopher Healey, Maneesh Agrawala,
    and Lawrence Anderson-Huang.

3
Visual perception
  • Structure of the Retina
  • Preattentive Processing
  • Detection
  • Estimating Magnitude
  • Change Blindness
  • Multiple Attributes
  • Gestalt

4
Visual perception and psychophysics
  • Psychophysics is concerned with establishing
    quantitative relations between physical
    stimulation and perceptual events.

5
Structure of the Retina
6
Structure of the Retina
  • The retina is not a camera!
  • Network of photo-receptorcells (rods and cones)
    andtheir connections

Anderson-Huang, L. http//www.physics.utoledo.edu
/lsa/_color/18_retina.htm
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
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.ed
u/lsa/_color/18_retina.htm
9
Preattentive Processing
10
How many 5s?
  • 385720939823728196837293827
  • 382912358383492730122894839
  • 909020102032893759273091428
  • 938309762965817431869241024

Slide adapted from Joanna McGrenere
http//www.cs.ubc.ca/joanna/
11
How many 5s?
  • 385720939823728196837293827
  • 382912358383492730122894839
  • 909020102032893759273091428
  • 938309762965817431869241024

12
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

13
Color (hue) is preattentive
  • Detection of red circle in group of blue circles
    is preattentive

image from Healey 2005
14
Form (curvature) is preattentive
  • Curved form pops out of display

image from Healey 2005
15
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
16
Healey appleton preattentive processing
  • http//www.csc.ncsu.edu/faculty/healey/PP/index.ht
    ml

17
Preattentive Visual Features
closure color (hue) intensity flicker direction
of motion stereoscopic depth 3D depth cues
  • line orientation
  • length
  • width
  • size
  • curvature
  • number
  • terminators
  • intersection

18
line (blob) orientation
19
length, width
20
closure
21
size
22
curvature
23
density, contrast
24
intersection
25
terminators
26
flicker
27
direction of motion
28
velocity of motion
29
Cockpit dials
  • Detection of a slanted line in a sea of vertical
    lines is preattentive

30
Detection
31
Just-Noticeable Difference
  • Which is brighter?

32
Just-Noticeable Difference
  • Which is brighter?

(130, 130, 130)
(140, 140, 140)
33
Webers Law
  • In the 1830s, 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 ?S to the initial stimulus S was
    relatively constant
  • ?S / S k

34
Webers 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.

35
Webers Law
  • Most continuous variations in magnitude are
    perceived as discrete steps
  • Examples contour maps, font sizes

36
Estimating Magnitude
37
Stevens Power Law
  • Compare area of circles

38
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 gt 1 overestimate
  • b lt 1 underestimate

graph from Wilkinson 99
39
Stevens Power Law
  • Stevens 1961

40
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)

41
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
42
Relative Magnitude Estimation
  • Most accurate
  • Least accurate
  • Position (common) scale
  • Position (non-aligned) scale
  • Length
  • Slope
  • Angle
  • Area
  • Volume
  • Color (hue/saturation/value)

43
Change Blindness
44
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/re
    nsink/flicker/

45
Possible Causes of Change Blindness
Simons, D. J. (2000), Current approaches to
change blindness, Visual Cognition, 7, 1-16.
46
Multiple Visual Attributes
47
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/
48
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.

49
Integral vs. Separable Dimensions
  • Integral
  • Separable

Ware 2000
50
Gestalt
51
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52
Gestalt
  • This law says that we try to experience things in
    as good a gestalt way as possible. In this sense,
    "good" can mean several things, such as regular,
    orderly, simplistic, symmetrical, etc. The other
    gestalt laws are

53
Gestalt Principles
  • figure/ground
  • proximity
  • similarity
  • symmetry
  • connectedness
  • continuity
  • closure
  • common fate
  • transparency

54
Figure-ground
  • Figure-ground minds have an innate tendency to
    perceive one aspect of an event as the figure or
    foreground and the other as the ground or the
    background.

55
proximity
56
similarity
57
symmetry
58
connectedness
59
continuity
60
closure
61
Classical Principles of Grouping (I)
62
Classical Principles of Grouping (II)
63
Examples
Proximity
Connectedness from Ware 2004
  • Figure/Ground

http//www.aber.ac.uk/media/Modules/MC10220/vispe
r07.html
64
Visual Completion
65
Edge Relatability
66
Illusory Contours
5.3.2
67
Illusory Contours (II)
68
Depth perception
  • Oculomotor
  • Acoomodation
  • Covegence
  • muscle feedback
  • control signal
  • Visual
  • Binocular
  • Monocular
  • Static cues
  • Interposition
  • Size
  • Perspective
  • Motion parallax

69
Depth perception
  • Perspective
  • Linear perspective
  • Texture gradient
  • Aerial-perspective
  • Shadow

70
Size
71
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72
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73
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74
Linear perspective
75
Aerial Perspective
76
Texture gradient
77
Shades and Shadows
78
Shades and Shadows
79
Overlapping
80
Motion
81
motion parallax
82
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83
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.

84
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