Visual perception
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Visual Perception . Cecilia R. Aragon IEOR 170 UC Berkeley Spring 2006. Acknowledgments. Thanks to slides and publications by Pat Hanrahan, Christopher Healey, Maneesh Agrawala, and Lawrence Anderson-Huang. Visual perception. Structure of the Retina Preattentive Processing Detection

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Visual perception

Visual Perception

Cecilia R. Aragon

IEOR 170

UC Berkeley

Spring 2006


Acknowledgments

Acknowledgments

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

IEOR 170


Visual perception1

Visual perception

  • Structure of the Retina

  • Preattentive Processing

  • Detection

  • Estimating Magnitude

  • Change Blindness

  • Multiple Attributes

  • Gestalt

IEOR 170


Visual perception and psychophysics

Visual perception and psychophysics

Psychophysics is concerned with establishing quantitative relations between physical stimulation and perceptual events.

IEOR 170


Structure of the retina

Structure of the Retina

IEOR 170


Structure of the retina1

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]

IEOR 170


Photo transduction

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]

IEOR 170


Electric currents from photo receptors

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]

IEOR 170


Preattentive processing

Preattentive Processing


How many 5 s

How many 5’s?

385720939823728196837293827

382912358383492730122894839

909020102032893759273091428

938309762965817431869241024

[Slide adapted from Joanna McGrenere http://www.cs.ubc.ca/~joanna/ ]

IEOR 170


How many 5 s1

How many 5’s?

385720939823728196837293827

382912358383492730122894839

909020102032893759273091428

938309762965817431869241024

IEOR 170


Preattentive processing1

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

IEOR 170


Color hue is preattentive

Color (hue) is preattentive

  • Detection of red circle in group of blue circles is preattentive

[image from Healey 2005]

IEOR 170


Form curvature is preattentive

Form (curvature) is preattentive

  • Curved form “pops out” of display

[image from Healey 2005]

IEOR 170


Conjunction of attributes

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]

IEOR 170


Healey applet on preattentive processing

Healey appleton preattentive processing

http://www.csc.ncsu.edu/faculty/healey/PP/index.html

IEOR 170


Preattentive visual features

line orientation

length

width

size

curvature

number

terminators

intersection

Preattentive Visual Features

closure

color (hue)

intensity

flicker

direction of motion

stereoscopic depth

3D depth cues

IEOR 170


Cockpit dials

Cockpit dials

  • Detection of a slanted line in a sea of vertical lines is preattentive

IEOR 170


Detection

Detection

IEOR 170


Just noticeable difference

Just-Noticeable Difference

  • Which is brighter?

IEOR 170


Just noticeable difference1

Just-Noticeable Difference

  • Which is brighter?

(130, 130, 130)

(140, 140, 140)

IEOR 170


Weber s law

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

IEOR 170


Weber s law1

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.

IEOR 170


Weber s law2

Weber’s Law

  • Most continuous variations in magnitude are perceived as discrete steps

  • Examples: contour maps, font sizes

IEOR 170


Estimating magnitude

Estimating Magnitude

IEOR 170


Stevens power law

Stevens’ Power Law

  • Compare area of circles:

IEOR 170


Stevens power law1

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]

IEOR 170


Stevens power law2

[Stevens 1961]

Stevens’ Power Law

IEOR 170


Stevens power law3

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)

IEOR 170


Stevens power law4

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]

IEOR 170


Relative magnitude estimation

Most accurate

Least accurate

Position (common) scale

Position (non-aligned) scale

Length

Slope

Angle

Area

Volume

Color (hue/saturation/value)

Relative Magnitude Estimation

IEOR 170


Change blindness

Change Blindness

IEOR 170


Change blindness1

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/

IEOR 170


Possible causes of change blindness

Possible Causes of Change Blindness

[Simons, D. J. (2000), Current approaches to change blindness, Visual Cognition, 7, 1-16. ]

IEOR 170


Multiple visual attributes

Multiple Visual Attributes

IEOR 170


The game of set

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/]

IEOR 170


Multiple visual attributes1

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.

IEOR 170


Integral vs separable dimensions

Integral vs. Separable Dimensions

Integral

Separable

[Ware 2000]

IEOR 170


Gestalt

Gestalt

IEOR 170


Gestalt principles

Gestalt Principles

  • figure/ground

  • proximity

  • similarity

  • symmetry

  • connectedness

  • continuity

  • closure

  • common fate

  • transparency

IEOR 170


Examples

Examples

Figure/Ground

Proximity

Connectedness [from Ware 2004]

[http://www.aber.ac.uk/media/Modules/MC10220/visper07.html]

IEOR 170


Conclusion

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.

IEOR 170


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