VisualizationVisualization

Perceptual and cognitive aspects

15th of September, 2010

Stefan Seipel

Overview

Quick overview over this lesson

Physiology of the human eye

Visual acuity and performance

Color, brightness and contrast

Use of colors

Pop-out effect

Cognitive limits

Physiology

RetinaReceptors of two types : cones and rods

Rods (sv. stavar):Sensitive at low light levelApproximately 100 millionContribute little at daylight (overloaded at daylight levels)Are interconnected over larger areas

Cones (sv. tappar): Effective at daylight levelsColor sensitiveAre highly packet at the fovea (180 per degree)Approx. 100.000 at the foveaApproximately 6 million in total

Retina

Blind spotAt approx. 15 degrees lateralExperiment: Two thumbs -> follow instructions

Fovea1,5-2 degrees

Corresponds to an area size s=2,5 cmat d=70 cm viewing distance

Visual Angle

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⎜⎝⎛⋅⋅=

2tan2 αds

Definition

Visual angle is the angle subtended by an object at some distance to the observer.

When describing visual acuities and properties, visual angle is used because it is independent of viewing distances and objects viewed.

Visual Angle

Focal field of view defined 1-2 degrees visual angle

Size of a thumbnail at approximately arms length

~1,5 cm at 60 cm viewing distance

Sensor density of 20 arc sec. (see above)

“receptor footprint” -> 0.06 mm at 60 cm viewing distance

Visual AcuitiesPoint acuity: 1 minute of arc

Grating acuity: 1-2 minutes of arc

Letter acuity: 5 minutes of arc (5,8 mm at 4 meters distance)

Stereo acuity: 10 seconds of arc

Vernier acuity: 10 seconds of arc

Acuity fall-off across visual field: Compare figure separate slide

Several receptors interconnected -> super-acuity

Acuity depends on brightness/contrast

Acuity depends on color (e.g. weak blue)

Visual Acuities

Point acuity: 1 minute of arc Grating acuity: 1-2 minutes of arcLetter acuity: 5 minutes of arc (5,8 mm at 4 meters distance)Vernier acuity: 10 seconds of arc

• Acuity fall-off across visual field: Compare figure

• Several receptors interconnected -> superacuity

• Acuity depends on brightness/contrast

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Fove

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Blin

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NoseTemple

Fove

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NoseTempleR

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Distance from fovea (in degrees visual angle)

Visual AcuitiesUtilisation of Vernier acuity: Caliper scales

Visual Acuities – Some illusionsExperiment: Visual illusion due to limited retinal resolution

First: Look at this image in fullscreen (15” monitor at 70cm viewing distance)Second: Step back about 4 meters from the screen.

What happens; can you explain?

Visual Acuities – Some illusions

The low-frequency component of the image. At far viewing distances they become prominent as the high frequency spatial

Components in the image cannot be resolved by the HVS.

Lens

Chromatic aberration

Power depends on color

Blurry blue

Blue appears “out of focus”

Receptor sensitivity for blue is only 5% of

maximum sensitivity for green

Dispersion caused by varying refractive index for different wavelengths

Refraction of light depends on• optical power of the lens• wavelength of the light

Can you read this?

Can you read this?

Can you read this?

Properties of the visual field of view

Periphery (horizontally up to 200 deg.)

Central FoV (vertically approx. 120 deg.)

Receptor distribution and properties

Stereo-overlap (approx. 120 deg.)

Most prominent figures at 4-5 deg visual angle

Approximately 6 cm at 70 cm viewing distance

Rapid changes are detected in periphera field of view

Luminance, lightness and brightness

Definitions:

Luminance is the measurable amount of light coming from some region in space . It is a physical property that can be exactly measured (eg. Candela per square meter).

Brightness is the perceived amount of light coming from self-luminous objects.

Lightness refers to the perceived reflectance of a surface. A white surface Is light a black one is dark.

Perception of brightness levels

The human visual system is not an absolute measuring device.

The perceived lightness and brightness depends on a number of factors:

• Overall ambient light level adjustment (photo pigment bleaching)

• The illuminant and spatial illumination conditions (see illusion next slide)

• Colors in the surround of an object (see illusion picture)

• Local contrast effects

Example:

A black object on a sunny day outside reflects more light than a white object inside an office room. Yet, we perceive the black object as dark and the white one as light.

Colors maps

Estimation of the lightness of colors depends on surround

Colors maps

Color not useful as a means to encode/read absolute value

Interpretation of color

Again, the human visual system is not an absolute measuring device.

Also perceived color depends on a number of factors:

• Overall ambient light level adjustment (photo pigment bleaching)

(after images)

• Colors in the surround of an object (see illusion picture)

• Local contrast effects

Color AdaptationWhat color is the shirt of the lady not raising her hands?

Color AdaptationLet’s have a look at a picture with a color filter.

What color is the top of the lady not raising her hands?

Did you say yellow? Right!

Color AdaptationHere is the original image, without filter.

And quite right. The color is yellow!

Color AdaptationNow lets copy the top from picture1 into the original picture2?

Well, the color of the top in picture1 was in fact green!

Color AdaptationHere is the direct comparison

ContrastVisual perception is not directly based on the neural signals ofthe receptors in the retina, instead there is some neural processing in several layers of retinal ganglion cells.

Contrast

Ganglion cells are organized with circular receptive fields thatcan have an on-center or off center. Size of receptive fields vary from central field of view to periphery.

Lateral inhibition (Hartline 1940)

ContrastDifference of Gaussian model (compare figure 3.3)

Simultaneous contrast

The DOG processing model yields enhanced contrast -> simultaneous contrast

Color Ramp example

Other illusionary pictures

Hermann Grid

High Contrast and Visual Stress

Spatial frequency of 3 deg / vis angle

And high contrast

See next picture

Tri-stimulus color model

Spectral range of visible light 380nm – 680nm

Spectral sensitivity function

Three peaks: 430 nm, 540nm, 580nm

Relative sensitivity of the eye

Green 555 nm, peakBlue 450 nm, 4% of max sensitivity

=> Blue is not a good choice in presence of green or red

Relative sensitivity to different wavelength according to CIE (V(l) (Values from Ware 2005)

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Tri-stimulus color model

Opponent Process Theory

Ewald Hering (1920)

• Six base colors (unlike trichromacy theory)

• Differential and additive processing of receptors signals

• Naming-, cultural and neurophysiologicalevidence for this theory

Cone signals are hierarchically combined and processed in three channels:

Yellow-Blue (R+G-B)

Red-Green (R-G)

Black-White (R+G+B)

Color as label

Ethnographic studies

Most frequent colors

How many we can distinguishCompare 4.12

Colors that are not basic are difficult to remember(orange, lime green …)

Criteria for use of color as labelDistinctness, uniqueness, contrast with background, color blindness, number, field size,conventions

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BrownPinkPurpleOrangeGray

Color as labelConventions and learned knowledge

Yellow

Green

Blue

Orange

Gray

Red

Green

Name the colors of the words!

Color as labelConventions and learned knowledge

Yellow

Green

Blue

Orange

Gray

Red

Green

Name the colors of the words!

Colors to show detail

Lightness contrast most important for readability of text and fine detail

Note: Acuity depending on brightness of colors

Not too small structures

Colors as visual pop-out

Visual pop-out:

Visual pop-out occurs when visual features are processed pre-attentively. I.e. in a visual task, where visual targets are identified, this identification is not depending on the number of the distractors (non-target elements).

Chrominance differences are useful as visual pop-out, however consider color restrictions according to 4.19

Colors maps

Perceptual linearity

Constant lightness contrast

Color maps for deviation detection

Not suited for quantitative assessment

VisualizationVisualizationPotential and pitfalls Potential and pitfalls

Visualization has an enormous potential!

”An image tells more than thousand words”

But:

”The eye sees what it wants to see”

CAVEAT: Illusions and perceptual limits

VisualizationVisualizationAmbiguous representations Ambiguous representations

”The eye sees what it wants to see”

Sax player or woman's face? Seal or donkey's face? Bacchus or couple kissing?

How you interpret the visual percept depends among others upon your personal attitude, expectations and visual angle

VisualizationVisualizationCognitive limits Cognitive limits

Visualizations have enormous potential!

”An image tells more than thousand words”

However:

”Human’s capacity for attention is limited”

Example: “Inattentional blindness”

InattentionalInattentional blindnessblindnessTask : Count the passes of the black team in the following video!

Visualizations have enormous potential!

”An image tells more than thousand words”

However:

”Human visual short term memory is limited”

Example: “Change blindness”

VisualizationVisualizationCognitive limits Cognitive limits

VisualizationVisualization

Change Blindness:

Large changes in a scene are not detected if they coincide with some visual disruption (saccades, blinks, transient noise and distraction)

Failure to compare relevant visual information from current scene with visual short term memory.

Change Blindness:

VisualizationVisualization

Change Blindness:

VisualizationVisualizationPotential pitfalls Potential pitfalls

The way in which data is mapped upon visual form affects how a message is perceived!

Visualizations can unintentionally make interpretation more difficult!

Visualizations can be manipulative or even be misused!

VisualizationVisualizationExample of manipulative useExample of manipulative use

Same data, different appearance!

“WiLLY:s Sveriges billigaste matkasse”, UNT ad 26th aug. 2010

This is what EXCEL offers you as default! After manual adjustment of scale.