Visual Perception Rich Clarke Q: Why should we care about humans in - - PowerPoint PPT Presentation

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Visual Perception Rich Clarke Q: Why should we care about humans in - - PowerPoint PPT Presentation

Visual Perception Rich Clarke Q: Why should we care about humans in the loop? A: Imagine building VR system... Asked to specify the ultimate, fully immersive visual display device. Want the Virtual World to be utterly indistinguishable


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Visual Perception

Rich Clarke

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Q: Why should we care about humans in the loop? A: Imagine building VR system...

  • Asked to specify the ultimate, fully immersive visual display device.
  • Want the Virtual World to be utterly indistinguishable from reality
  • I.e. what are the hard limits on our perception of reality?
  • What’s the best that we need to do?
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How to start to answer this question?

  • Basic visual hardware: Visual anatomy & physiology
  • The fundamental unit of visual coding: Receptive fields
  • Visual pathways: The split of information streams
  • Brief aside: How do photoreceptors change EM radiation into neural

activity?

  • How well can you really see? Resolution and acuity
  • Seeing the sun and the stars: Brightness adaption
  • Colour perception

We’re going to keep in mind: The So What? Implications for Computer Graphics?

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The eye…

POSTERIOR: ~mesh of photoreceptors… ANTERIOR: Modelled as camera optics…

Basic visual hardware: Visual anatomy & physiology

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LIGHT

Pigmented layer

Photoreceptors in the retina: Rods & Cones

Basic visual hardware: Visual anatomy & physiology

Start of the ‘brain’… To the optic nerve

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  • Extremely sensitive to light
  • Provide achromatic vision
  • Work at low level (scotopic)

illumination

  • Large receptive fields
  • Peak absorbance (sensitivity)

at ~500nm

  • Less sensitive to light
  • Provide colour vision
  • Work at high level (photopic)

illumination

  • Three types:

‘B’ peak at 437nm, ‘G’ peak at 533nm, ‘R’ peak: 564nm Much smaller receptive fields

Basic visual hardware: Visual anatomy & physiology

Photoreceptors in the retina: Rods & Cones (2)

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  • Understanding of “hardware” gives insight into kinds of information that

can be coded

  • Real VR system: focus resource on right areas

Basic visual hardware: Visual anatomy & physiology

SO WHAT?

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The fundamental unit of visual coding: Receptive fields

Eye

‘On centre’ cells ‘Off centre’ cells Higher up in the brain (in V1): integrate simple cells: complex cells

A Cell’s Receptive Field

  • Defined by spatially localised group of

photoreceptors serving some ganglion cell

  • Location and quality of stimulus to which

the ganglion cell is responsive

  • Opponency:

On centre and off centre Spectral as well as spatial: Red/Green Yellow Blue Absolute physical values lost:

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Visual system encodes the “empirical significance” of the stimulus

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Maybe it’s an artefact of the centre surround receptive fields of cells – i.e. visual illusions are an unavoidable consequence of the mechanics

  • f our visual hardware

Recall last slide...

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Same local statistics…

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  • Basic building blocks of visual perception
  • Information about absolutes (both brightness and ‘colour’) lost –

contrast & context sensitivity only (c.f. illusions)

  • Brain ‘looks for’ fundamental structures that are/have been

behaviourally relevant in ontogenetic and phylogenetic history: fast ‘hardware’ recognition

The fundamental unit of visual coding: Receptive Fields

SO WHAT?

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Visual pathways: The split of information streams

LGN: 6 layers: Magnocellular layers – primary input from peripheral retina – non spectrally opponent ganglions, large receptive fields Parvocellular layers – primary input from the foveal region – spectrally opponent cells, small receptive fields

From the eye to the brain

Area V1 (Visual Cortex): more complex cells (I.e. with more complex receptive fields) Deals with What? And Where? …Separately?

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  • Fast response, achromatic system, motion sensitive, low res.

(Magnocellular layers)

  • Slow response trichromatic system, motion insensitive, high res.

(Parvocellular layers)

Visual pathways: The split of information streams

SO WHAT?

Eyes may be serving 2 relatively separate visual systems:

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How do photoreceptors change EM radiation into neural activity?

Rods & Cones: Outersegment: billions of light sensitive pigment molecules Molecules embedded in disks, stacked like pancakes Rods: Pigment is Rhodopsin γ

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How well can you really see? Resolution and acuity

  • 1. Real optical system: aberrations, diffraction at

entry aperture Resolution limited to 30arcsec

  • 2. Photoreceptors sample retinal image -> neural

image representation. Spacing well matched to optics (Sampling theory)

Physical limits on resolving power

Three things determine resolution: 1. Optical filtering, 2. receptor sampling, (and 3. receptive field organisation) Visual acuity is a function of contrast sensitivity ~30sec Vernier (hyper)acuity: Ability to localise position of

  • bjects – not a function of contrast sensitivity

Can detect misalignments of ~5sec Unknown exactly how it’s done

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How well can you really see? Resolution and acuity

SO WHAT?

  • Obviously sets hard limit on how much detail required of a

display system

  • VR systems not close to this for real-time display
  • Vernier acuity plays an important role in the visibility of aliasing

artefacts in digital images – simple analysis of the visual system would predict that some artefacts should not be seen (below the limit of supposed visual acuity)

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Seeing the sun and the stars: Brightness adaption

How many orders of magnitude difference between the dimmest and the brightest things we can see?

Brightness adaption

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Three mechanisms Mechanical

  • Pupil dilation

Photochemical

  • Bleaching & regeneration

Neural

  • Changes in processing

Changes in: Contrast Sensitivity: Pattern Acuity: Colour Perception

Seeing the sun and the stars: Brightness adaption

Brightness adaption (2)

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Seeing the sun and the stars: Brightness adaption

The time course of adaption

Purkeinje break

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Seeing the sun and the stars: Brightness adaption

SO WHAT?

  • Most of the information or 'power' (in Fourier domain) of an

image is in brightness contrast

  • Using 3 adaption mechanisms, able to see effectively over a

range of ~10 log units

  • At different luminances contrast sensitivity, acuity, colour

perception changes markedly

  • Obvious implications for the design of a VR system (resource

allocation etc.)

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Colour perception

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Colour perception

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Colour perception

What is colour perception? How do we (efficiently) recreate it?

Relative stimulation of each cone type in your retina (RGB) in the context of some visual field Different spectral distributions of light should be able to stimulate the photoreceptors identically: Receptor sensitivity SD b SD a Spectral distributions Distinct distributions that are perceived identically w.r.t some visual system - METAMERS

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Colour Perception

SO WHAT?

  • Sensible choice of some colour primaries should allow you to

re-create any visible colour simply (without recreating the whole C(λ) distribution

  • Not quite as simple as that…but right primaries will produce a

colour gamut that covers most visible colours

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Summary…

  • Understanding of “hardware”: insight into kinds of

information that can be coded

  • Receptive fields: Basic building blocks of visual perception
  • Resolution of human visual system sets limit on how

much detail required

  • At different luminances contrast sensitivity, acuity, colour

perception changes markedly

  • World is not seen “as it is”: Context important: need to

understand how scenes perceived

  • Colour: Metamers, colour primaries & limitations of colour

gamuts

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Refs, picture credits

Ref 1: [Ferwerder] Ferwerda, J. A. (2001) Elements of Early Vision for Computer Graphics, IEEE Computer Graphics and Applications, 21(5), pp. 22-33. Ref 2: [Atkinson] R.C. Atkinson, ed., Steven’s Handbook of Experimental Psychology, 2nd ed., John Wiley & Sons, New York, 1988. Ref 3: [Purves & Lotto] www.lottolab.org, also D. Purves & R. Beau Lotto, Why we see what we do: An Empirical Theory of Vision, Sinauer Associates, 2003 Ref 7: [Sekuler & Blake] 7. R. Sekuler and R. Blake, Perception, McGraw-Hill, New York, 1994. Ref 15: [Spillman & Werner] L. Spillman and J.S. Werner, eds., Visual Perception: The Neurophysiological Foundations, Academic Press, San Diego, 1990. Ref 28: [Bollin & Mayer] M.R. Bolin and G.M. Meyer, “A Frequency Based Ray Tracer,”

  • Proc. Siggraph 95, ACM Press, New York, 1995, pp. 409-418.