what is vision aristotle - vision is knowing what is where by looking

What is vision

• Aristotle - vision is knowing what is where by looking

What is vision


• Helmholtz - vision is an act of unconscious inference– Our percepts are inferences about properties of

the world from sensory data

What is vision




• Vision is (neural) computation

Processes of vision

What is vision




• Vision is (neural) computation

• Vision controls action

The swinging room

Processes of vision II

Lecture outline

• Image transduction

• Neural coding in the retina

• Neural coding in visual cortex

• Visual pathways in the brain

The Optic Array: pattern of light intensity arrivingat a point as a function of direction (), time () and wavelength()

I = f(

Goals of eye design• Form high spatial resolution image

– Accurately represent light intensities coming from different directions.

• E.g. minimize blur in a camera

• Maximize sensitivity– Trigger neural responses at very low light levels.– Particle nature of light places fundamental limit

on sensitivity.

Visual angle

Point spread

Point spread function

Resolution (acuity)

• Optics of eye and physics of light pace fundamental limit on acuity

• Width of blur circle in fovea = 1’

• Blur increases with eccentricity– Optical aberrations– Depth variation in the environment

Focus - the lens equation

f

di

do

lens power (diopters) = 1

f(meters)

lens power = 1f

=1do

+1di

Accommodation - bringing objects into focus

p1 p2

p1 p2

Focused on

Focused on

Some numbers

• Refractive power of cornea – 43 diopters

• Refractive power of lens– 17 (relaxed) - 25 diopters

• Other eyes– Diving ducks - 80 diopter accommodation range– Anableps - four eyes with different focusing power

Sampling in the fovea

• Receptor sampling in fovea matches the width of point spread function (blur circle)– Effective width of blur circle ~ 1 minute of arc– Spacing of receptors ~ .5 minutes of arc

(theoretical requirement for optimal resolution)

Relationship between sampling and blurTwo test images

60 cycle / degree grating 120 cycle / degree grating



Receptor sampling = .5 minutes



Receptor sampling = .5 minutes

Receptor Output

0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5

Peripheral sampling

• More rods than cones in periphery

• Coarser sampling in periphery

Tricks for maximizing resolution

Problem:

High resolution coding of intensity information

Example• Computer monitors typically use 8 bits to encode

the intensity of each pixel.– 256 distinct light levels

• Old monitors only provided 4 bits per pixel.– 16 distinct light levels

• Number of light levels encoded = intensity resolution of the system.

• Human visual system can only distinguish ~ 200 - 250 light levels.

Code wide range of light intensities

• Range of light intensities receptors can encode

• Dynamic range of receptors and of ganglion cells limits # of distinguishable light levels.

• Problem

– How does system represent large range of intensities while maintaining high intensity resolution?

10−6 −107candelas/ m2

Some typical intensity values

white paper in sunlight - 104

Video screen - 10−1 −102

white paper in moonlight- 10−2

white paper in starlight- 10−4

candelas / m2

Solution

• Dynamic range of receptors (cones)

– 10 - 1000 photons absorbed per 10 msec.

• Range of intensities in a typical scene

– 10-6 - 10-4 cd / m2 in starlight

– 102 - 104 cd / m2 in sunlight

– 100:1 range of light intensities

• Only need to code 100:1 range of intensities within a scene

• Solution - Adaptation adjusts dynamic range of receptors to match range of intensities in a scene.

# photons hitting receptor

% photonsabsorbed

# photonsabsorbed

Scene 1

Scene 2

10 - 1,000

1,000 - 100,000

100%

10%

10 - 1,000

10 - 1,000

Increase Illumination Adaptation

Starlight Moonlight

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

Window of visibility

Indoor lighting Sunlight

Starlight Moonlight Indoor lighting Sunlight

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


Adapt to the dark(e.g. % photons absorbed = .1)

Starlight Moonlight

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


Adapt to the bright(e.g. % photons absorbed = .000000001)

Indoor lighting Sunlight

Hartline Experiment

• Limulus eye has ommotidia containing one receptor each.

• Each receptor sends a large axon to the brain.

• Output of one receptor was inhibited by light shining on a neighboring receptor (lateral inhibition).

Ganglion cell receptive fields

• Receptive field - region of visual field that cell responds to.

• Center-surround receptive field

+++++

+++

- --

--

- --

--

----

--- -- - -- + +

++

+++

+++

+ ----

- --

On-center, off-surround Off-center, on-surround

Ganglion cells as computational devices

• Write a mathematical function that calculates firing rate of cell from luminance pattern.

• 1st guess – Increase in firing rate = weighted sum of

intensities within receptive field.

• Problem 1 - Adaptation• Problem 2 - dark regions in inhibitory region

actually excite cell


• Solution– Increase in firing rate = weighted sum of local

contrast values within receptive field.

• Local contrast

C(x,y) = I(x,y) / M - 1




• Local contrast

C(x,y) = I(x,y) / M - 1

Intensity




• Local contrast

C(x,y) = I(x,y) / M - 1

Intensity Mean intensity




• Local contrast

C(x,y) = I(x,y) / M - 1

Local contrast Intensity Mean intensity

+++

++

+ +++++

--

--

--

--

---

++++

- ---

---

--- -

-

-

Ganglion Cells Simple Cells

++

++

+ +++++

---

--

--

---

++

++

+ +++++

Cells in V1

• Simple cells– orientation selective– scale selective (cells have different size receptive

fields)– some are motion selective– some are end-stopped

• Complex cells– same properties as simple cells, BUT ...– insensitive to position of stimulus within RF

V1

V2

V3

MT

V4

MST Parietal Lobe

Temporal Lobe

Cortical pathways

what is vision aristotle - vision is knowing what is where by looking

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