Computer Graphics - The Human Visual System - Hendrik Lensch - - PowerPoint PPT Presentation

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Computer Graphics - The Human Visual System - Hendrik Lensch - - PowerPoint PPT Presentation

Feb 23, 2024 34 likes •538 views

Computer Graphics - The Human Visual System - Hendrik Lensch Computer Graphics WS07/08 Human Visual System Overview Last time Antialiasing Super-Sampling Today The Human Visual System The eye Early vision

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SLIDE 1

Computer Graphics WS07/08 – Human Visual System

Computer Graphics

  • The Human Visual System -

Hendrik Lensch

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SLIDE 2

Computer Graphics WS07/08 – Human Visual System

Overview

  • Last time

– Antialiasing – Super-Sampling

  • Today

– The Human Visual System

  • The eye
  • Early vision
  • High-level analysis
  • Color perception
  • Next lecture

– Color spaces

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SLIDE 3

Computer Graphics WS07/08 – Human Visual System

Light

  • Electromagnetic radiation
  • Visible spectrum: ~ 400 to 700 nm
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SLIDE 4

Computer Graphics WS07/08 – Human Visual System

Radiation Law

  • Physical model for light

– Wave/particle-dualism

  • Electromagnetic radiation wave model
  • Photons: Eph=hν

particle model & ray optics

– Plenoptic function

  • L= L(x, ω, t, ν, γ), 5 dimensional,

Ignored parameters:

  • No polarization
  • No fluorescence
  • Decoupling of the spectrum
  • Not time dependent
  • Instant propagation with

speed of light

  • no phosphorescence

Used parameters:

  • Direction
  • Location
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SLIDE 5

Computer Graphics WS07/08 – Human Visual System

Photometry

  • Equivalent units to radiometry

– Weight with luminous efficiency function V(λ) (luminous efficiency function) – Spectral or “total” units – Distinction in English simple:

  • “rad”: radiometric unit
  • “lum”: photometric unit

W lm K d V K

m e m

/ 680 ) ( ) (

v

= Φ = Φ

∫

λ λ λ

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SLIDE 6

Computer Graphics WS07/08 – Human Visual System

Radiometric Units

Strahlungsstärke radiant intensity [W/sr] Ie dQ/dωdt Intensität intensity Strahlungsdichte Radiance [W/m2/sr] Le dQ/dAΦdωdt

  • Radiom. Emissionsvermögen

Radiosity [W/m2] Me = Be dQ/dAdt Flußdichte flux density Bestrahlungsstärke Irradiance [W/m2] Ee dQ/dAdt Flußdichte flux density Strahlungsfluß radiant flux [W= J/s] Φe dQ/dt Leistung, Fluß power, flux Strahlungsenergie radiant energy [J= Ws] Joule Qe Energie energy Notation Unit Symbol Definition Specification

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SLIDE 7

Computer Graphics WS07/08 – Human Visual System

Photometric Units

With luminous efficiency function weighted units

Lichtstärke radiant intensity [cd (candela) = lm/sr] Iv dQ/dωdt Intensität intensity Leuchtdichte Luminance [lm/m2/sr] Lv dQ/dAΦdωdt

  • Photom. Emissionsvermögen

Luminosity [lux] [Mv=] Bv dQ/dAdt Flußdichte flux density Beleuchtungsstärke Illuminance [lux= lm/m2] Ev dQ/dAdt Flußdichte flux density Lichtstrom luminous flux [lm (Lumen) = talbot/s] Φv dQ/dt Leistung, Fluß power, flux Lichtmenge luminous energy [talbot] Qv Energie energy Notation Units Symbol Definition Specification

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SLIDE 8

Computer Graphics WS07/08 – Human Visual System

Luminance Range

Luminance [cd/m2]

10-6 10-4 10-2 100 102 104 106 108

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SLIDE 9

Computer Graphics WS07/08 – Human Visual System

Contrast (Dynamic Range)

Luminance [cd/m2]

10-6 10-4 10-2 100 102 104 106 108

Dynamic Range 1:500 1:1500 1:30

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SLIDE 10

Computer Graphics WS07/08 – Human Visual System

High Dynamic Range (HDR)

10-6 10-4 10-2 100 102 104 106 108

HDR Photo Usual Photo

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SLIDE 11

Computer Graphics WS07/08 – Human Visual System

Illumination: samples

  • Typical illumination intensities

5.000 – 10.000 TV studio 0.1 – 20 Street lighting 50 – 220 Home lighting 200 – 550 Office lighting 1.000 – 5.500 Shop lighting 0.0001 – 0.001 Starry night 0.01 – 0.1 Moon light 1 – 108 Sunset 2.000 – 27.000 Day light 25.000 – 110.000 Direct solar radiation Illumination intensity [lux] Light source

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SLIDE 12

Computer Graphics WS07/08 – Human Visual System

  • Percept. Effects – Vision

Modes

Simulation requires:

– control over color reproduction – local reduction of detail visibility (computationally expensive)

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SLIDE 13

Computer Graphics WS07/08 – Human Visual System

  • Percept. Effects – Light

Adaptation

Adaptation to dark much slower Simulation requires:

– time-dependent filtering of light adaptation

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SLIDE 14

Computer Graphics WS07/08 – Human Visual System

Human Visual Perception

  • Determines how real-world scenes appear to us
  • Understanding of visual perception is necessary

to reproduce appearance in tone mapping

early vision (eyes) image appearance

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SLIDE 15

Computer Graphics WS07/08 – Human Visual System

Distribution of Rods and Cones

  • approximate a Poisson disc distribution
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SLIDE 16

Computer Graphics WS07/08 – Human Visual System

Human Visual System

  • Physical structure well established
  • Perceptual behaviour is a complex process
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SLIDE 17

Computer Graphics WS07/08 – Human Visual System

Human Visual System

  • Physical structure well established
  • Perceptual behaviour is a complex process
  • ptic chiasm
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SLIDE 18

Computer Graphics WS07/08 – Human Visual System

HVS - Relationships

Stimulus Psychophysics Physiology Perception Neural response

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SLIDE 19

Computer Graphics WS07/08 – Human Visual System

Perception and Eye

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SLIDE 20

Computer Graphics WS07/08 – Human Visual System

Retina

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SLIDE 21

Computer Graphics WS07/08 – Human Visual System

Eye as a Sensor

  • Relative Sensitivity of Cones

– S scaled by 3x – Z (Zäpfchen – cones) total sensitivity

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SLIDE 22

Computer Graphics WS07/08 – Human Visual System

Eye

  • Fovea:

– Ø 1-2 visual degrees – 6-7 Mio. cones, about 0.4 arc seconds wide – No rods, but three different cone types:

  • L(ong, 64%), M(edium, 32%), S(hort wavelength, 4%)
  • Results in varying resolution depending on color
  • Resolution: 10 arc minutes (S, blue), 0.5 arc minutes (L, M)

– Linked directly with optical nerves – Adaptation of light intensity only through cones

  • Periphery:

– 75-150 Mio. rods, night vision, S/W – Response to stimulation of approx. 5 photons/sec. (@ 500 nm) – Many thousands of cells are combined before linked with nerves

  • Bad resolution
  • Good flickering sensitivity
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SLIDE 23

Computer Graphics WS07/08 – Human Visual System

This is a text in red This is a text in green This is a text in blue

This is a text in red This is a text in green This is a text in blue

This is a text in red This is a text in green This is a test in blue

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SLIDE 24

Computer Graphics WS07/08 – Human Visual System

Visual Acuity

Resolution in line-pairs/arc minute Receptor density

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SLIDE 25

Computer Graphics WS07/08 – Human Visual System

Resolution of the Eye

  • Resolution-experiments

– Line pairs: 50-60/degree resolution .5 arc minutes – Line offset: 5 arc seconds (hyperacuity) – Eye micro-tremor: 60-100 Hz, 5 μm (2-3 photoreceptor spacings)

  • Allows to reconstruct from super-resolution

– Together corresponds to

  • 19“ display at 60 cm: 18.0002 Pixel (30002 w/out hyperacuity)
  • Automatic fixation of eye onto region of interest

– Automatic gaze tracking – Apparent overall high resolution of fovea

  • Visual acuity increased by

– Brighter objects – High contrast

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SLIDE 26

Computer Graphics WS07/08 – Human Visual System Campbell-Robson contrast sensitivity chart

Luminance Contrast Sensitivity

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SLIDE 27

Computer Graphics WS07/08 – Human Visual System

Contrast Sensitivity

  • Sensitivity:

1 / threshold contrast

  • Maximum acuity at

5 cycles/degree (0.2 %)

– Decrease toward low frequencies: lateral inhibition – Decrease toward high frequencies: sampling rate (Poisson disk) – Upper limit: 60 cycles/degree

  • Medical diagnosis

– Glaucoma (affects peripheral vision: low frequencies) – Multiple sclerosis (affects optical nerve: notches in contrast sensitivity)

www.psychology.psych.ndsu.nodak.edu

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SLIDE 28

Computer Graphics WS07/08 – Human Visual System

Color Contrast Sensitivity

  • Color vs. luminance

vision system

– Higher sensitivity at lower frequencies – High frequencies less visible

  • Image compression
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SLIDE 29

Computer Graphics WS07/08 – Human Visual System

Threshold Sensitivity Function

l

  • g

l

  • g

Δ Δ Δ Δ L L TVI function

rod cone

2 4 6

  • 2
  • 4
  • 6
  • 2

2 4

log L log L

L+ΔL L

  • Weber-Fechner Law (Treshhold Versus Intensity, TVI)

– Perceived brightness = log (radiant intensity)

E=K+c log Iv

– Perceivable intensity difference

  • 10 cd vs. 12 cd: ΔL=2cd
  • 20 cd vs. 24 cd: ΔL=4cd
  • 30 cd vs. 36 cd: ΔL=6cd
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SLIDE 30

Computer Graphics WS07/08 – Human Visual System

Weber-Fechner Examples

104/103 105/103 106/103 207/206 208/206 209/206

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SLIDE 31

Computer Graphics WS07/08 – Human Visual System

Mach Bands

  • “Overshooting“ along edges

– Extra-bright rims on bright sides – Extra-dark rims on dark sides

  • Due to “Lateral Inhibition“
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SLIDE 32

Computer Graphics WS07/08 – Human Visual System

Lateral Inhibition

  • Pre-processing step within retina

– Surrounding brightness level weighted negatively

  • A: high stimulus, maximal bright inhibition
  • B: high stimulus, reduced inhibition stronger response
  • D: low stimulus, maximal inhibition
  • C: low stimulus, increased inhibition

weaker response

  • High-pass filter

– Enhances contrast along edges – Difference-of-Gaussians (DOG) function

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SLIDE 33

Computer Graphics WS07/08 – Human Visual System

Lateral Inhibition: Hermann Grid

  • Dark dots at crossings
  • Explanation

– Crossings (A)

  • More surround stimulation

(more bright area) ⇒ Less inhibition ⇒ Weaker response

– Streets (B)

  • Less surround stimulation

⇒ More inhibition ⇒ Greater response

  • Simulation

– Darker at crossings, brighter in streets – Appears more steady – What if reversed ?

A B

Simulation

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SLIDE 34

Psychedelic

some further weirdness

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Computer Graphics WS07/08 – Human Visual System

High-Level Contrast Processing

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Computer Graphics WS07/08 – Human Visual System

High-Level Contrast Processing

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SLIDE 37

Computer Graphics WS07/08 – Human Visual System

Cornsweet Illusion

  • Apparent contrast due to gradual darkening /

brightening towards a contrasting edge

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SLIDE 38

Computer Graphics WS07/08 – Human Visual System

  • Percept. Effects – Veiling Glare

Simulation requires:

– scatter (blur) of sources of high luminance (computationally expensive)

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SLIDE 39

Computer Graphics WS07/08 – Human Visual System

Shape Perception

http://www.panoptikum.net/optischetaeuschungen/index.html

  • Depends on surrounding

primitives

– Directional emphasis – Size emphasis

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SLIDE 40

Computer Graphics WS07/08 – Human Visual System

Shape Processing: Geometrical Clues

http://www.panoptikum.net/optischetaeuschungen/index.html

  • Automatic geometrical interpretation

– 3D perspective – Implicit scene depth

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SLIDE 41

Computer Graphics WS07/08 – Human Visual System

Visual “Proofs”

http://www.panoptikum.net/optischetaeuschungen/index.html

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SLIDE 42

Computer Graphics WS07/08 – Human Visual System

HVS: High-Level Scene Analysis

http://www.panoptikum.net/optischetaeuschungen/index.html

  • Experience
  • Expectation
  • Local clue consistency
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SLIDE 43

Computer Graphics WS07/08 – Human Visual System

Impossible Scenes

http://www.panoptikum.net/optischetaeuschungen/index.html

  • Escher et.al.

– Confuse HVS by presenting contradicting visual clues

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SLIDE 44

Computer Graphics WS07/08 – Human Visual System

Single Image Random Dot Stereograms

  • Vergence: both eyes rotate to look at the same spot
  • Accommodation: focussing at a particular depth plane
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Computer Graphics WS07/08 – Human Visual System

SIRDS Construction

p0 p1L p1R p2L p2R

– Assign arbitrary color to p0 in image plane – Trace from eye points through p0 to object surface – Trace back from object to corresponding

  • ther eye

– Assign color at p0 to intersection points p1L,p1R with image plane – Trace from eye points through p1L,p1R to

  • bject surface

– Trace back to eyes – Assign p0 color to p2L,p2R – Repeat until image plane is covered

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SLIDE 46

Computer Graphics WS07/08 – Human Visual System

Another Optical Illusion

  • If you stare for approx. 20 seconds some of you will

actually see a giraffe.

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SLIDE 47

Computer Graphics WS07/08 – Human Visual System

Virtual Movement

caused by saccades, motion from dark to bright areas

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SLIDE 48

Computer Graphics WS07/08 – Human Visual System

Color

  • Physics

– Continuous spectral energy distribution

  • Human color perception

– Cones in retina – 3 different cone types – Spectral mapping to 3 channels

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SLIDE 49

Computer Graphics WS07/08 – Human Visual System

Visual Acuity and Color Perception

Photopic vision Scotopic/mesopic transition Mesopic/photopic transition Scotopic vision

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Computer Graphics WS07/08 – Human Visual System

Color Perception

  • Di-chromaticity (dogs, cats)

– Yellow & blue-violet – Green, orange, red indistinguishable

  • Tri-chromaticity (humans, monkeys)

– Red, green, blue – Color-blindness

  • Most often men, green color-blindness

www.lam.mus.ca.us/cats/color/ www.colorcube.com/illusions/clrblnd.html