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What is vision

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

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What is vision

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  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

  3. 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

  4. Processes of vision

  5. 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

  6. The swinging room

  7. Processes of vision II

  8. Lecture outline • Image transduction • Neural coding in the retina • Neural coding in visual cortex • Visual pathways in the brain

  9. The Optic Array: pattern of light intensity arriving at a point as a function of direction (q, W), time (t) and wavelength(l) I = f(q, W, t, l)

  10. 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.

  11. Visual angle

  12. Point spread

  13. Point spread function

  14. 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

  15. Focus - the lens equation

  16. Accommodation - bringing objects into focus Focused on Focused on

  17. 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

  18. 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)

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

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

  21. Relationship between sampling and blur Two test images 120 cycle / degree grating 60 cycle / degree grating Receptor sampling = .5 minutes .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 Receptor Output

  22. Peripheral sampling • More rods than cones in periphery • Coarser sampling in periphery

  23. Tricks for maximizing resolution

  24. Problem: High resolution coding of intensity information

  25. 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.

  26. 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?

  27. Some typical intensity values

  28. 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.

  29. # photons absorbed % photons absorbed # photons hitting receptor 10 - 1,000 Scene 1 10 - 1,000 100% Increase Illumination Adaptation 10 - 1,000 10% 1,000 - 100,000 Scene 2

  30. Window of visibility Sunlight Indoor lighting Moonlight Starlight 102 106 104 10 10-2 10-4 10-6

  31. Window of visibility Adapt to the dark (e.g. % photons absorbed = .1) Sunlight Indoor lighting Moonlight Starlight 102 106 104 10 10-2 10-4 10-6

  32. Window of visibility Adapt to the bright (e.g. % photons absorbed = .000000001) Sunlight Indoor lighting Moonlight Starlight 102 106 104 10 10-2 10-4 10-6

  33. 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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