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What is vision Aristotle - vision is knowing what is where by looking.

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Presentation on theme: "What is vision Aristotle - vision is knowing what is where by looking."— Presentation transcript:

1 What is vision Aristotle - vision is knowing what is where by looking

2 What is vision Aristotle - vision is knowing what is where by looking Helmholtz - vision is an act of unconscious inference –Our percepts are inferences about properties of the world from sensory data

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4 What is vision Aristotle - vision is knowing what is where by looking Helmholtz - vision is an act of unconscious inference –Our percepts are inferences about properties of the world from sensory data Vision is (neural) computation

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7 Processes of vision

8 What is vision Aristotle - vision is knowing what is where by looking Helmholtz - vision is an act of unconscious inference –Our percepts are inferences about properties of the world from sensory data Vision is (neural) computation Vision controls action

9 The swinging room

10 Processes of vision II

11 Lecture outline Image transduction Neural coding in the retina Neural coding in visual cortex Visual pathways in the brain

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13 The Optic Array: pattern of light intensity arriving at a point as a function of direction (  ), time (  ) and wavelength( ) I = f( 

14 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.

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16 Visual angle

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21 Point spread

22 Point spread function

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24 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

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26 Focus - the lens equation

27 Accommodation - bringing objects into focus Focused on

28 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

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33 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)

34 Relationship between sampling and blur Two test images 60 cycle / degree grating 120 cycle / degree grating

35 Relationship between sampling and blur Two test images 60 cycle / degree grating 120 cycle / degree grating Receptor sampling =.5 minutes

36 Relationship between sampling and blur Two test images 60 cycle / degree grating 120 cycle / degree grating Receptor sampling =.5 minutes Receptor Output

37 Peripheral sampling More rods than cones in periphery Coarser sampling in periphery

38 Tricks for maximizing resolution

39 Problem: High resolution coding of intensity information

40 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 ~ light levels.

41 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?

42 Some typical intensity values

43 Solution Dynamic range of receptors (cones) – photons absorbed per 10 msec. Range of intensities in a typical scene – cd / m 2 in starlight – cd / m 2 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.

44 # photons hitting receptor % photons absorbed # photons absorbed Scene 1 Scene ,000 1, , % 10% ,000 Increase IlluminationAdaptation

45 Starlight Moonlight Window of visibility Indoor lighting Sunlight

46 Starlight Moonlight Indoor lighting Sunlight Window of visibility Adapt to the dark (e.g. % photons absorbed =.1)

47 Starlight Moonlight Window of visibility Adapt to the bright (e.g. % photons absorbed = ) Indoor lighting Sunlight

48 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).

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51 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

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53 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

54 Ganglion cells as computational devices Solution –Increase in firing rate = weighted sum of local contrast values within receptive field. Local contrast C(x,y) = I(x,y) / M - 1

55 Ganglion cells as computational devices Solution –Increase in firing rate = weighted sum of local contrast values within receptive field. Local contrast C(x,y) = I(x,y) / M - 1 Intensity

56 Ganglion cells as computational devices Solution –Increase in firing rate = weighted sum of local contrast values within receptive field. Local contrast C(x,y) = I(x,y) / M - 1 Intensity Mean intensity

57 Ganglion cells as computational devices 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 Intensity Mean intensity

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62 Ganglion Cells Simple Cells

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64 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

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75 V1 V2 V3 MT V4 MST Parietal Lobe Temporal Lobe Cortical pathways

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