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Flashcards in Color and Motion Slides Deck (68)
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1
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The light reach the eye from a surfact is the product of the light falling on a surface and reflectance of the surface.

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3
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Illustration of the distribution of the three types of cone photoreceptors in the human fovea.

4
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Spectral sensitivies of fthe three classes of cone photoreceptor.

5
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The response of a receptor is the product of the intensity of the light and the sensitivity of the receptor. The thick arrow and the dashed arrow pointing to the left show the response of the receptor to a particular wavelength (one that looks organce to us). The black curve shows what the response of the receptor would be at each wavelength, assuming each wavelength presented to the eye has the same physical intensity.

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Here we see that a blue wavelength and an orange wavelength of the same intensity produce the same response. This illustrates the principle of univariance: a receptor’s response only signals how much total light is absorbed not which wavelenghts are in the light. Having only one type of receptor would make telling the difference between lights impossible on the basis of wavelength alone. For example, switching between the orance and blue light in this case would not produce a change in the response of the receptor.

7
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A numerical example of calculating the response from the intensity of a pure wavelength and the spectral sensitivity curve of the receptor. Notice that with only one receptor type, every wavelength can be adjusted in intensity to produce the same response as any other wavelength. Therefore, at night when only the rod receptors are active, every wavelength can appear the same to us as every other wavelength. Ths is otal color blindness.

8
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Color vision is possible with more than one receptor type because two wavelengths cannot produce the same responses in all types of receptor at the same time. Notice how the patter of responses is very different for the orange and blue wavelengths.

9
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Because we have only three types of photoreceptors our color vision is very limited. Those limitation shave been studied in detail with color mixture experiments. This slide shows three projectors adding three different colored lights on a screen.

10
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The additive color mixture experiment. A test light is projected on the left and the subject adjusts the intensities of three primary lights to match the appearance of the test light.

11
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Additive color mixtures is usually done by adding lights together. This might be done with projectors or with small phosphor dots such as those in TV or computer display.

12
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Color subtraction

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subtractive color mixture is what happens when pigments are mixed together.

14
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Additive color mixure is possible with pigments, if the pigments are painted in different (non-overlapping) locations and the image is viewed from far away.

15
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Principle of color matching

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Two lights will look identical in color if the responses of all receptor types are the same for two lights.

16
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Dichromacy

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Any light can be mimicked (reproduced) by an additive mixture of two primary lights.

17
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Trichromacy

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Any light can be mimicked (reproduced) by an additive mixture of three primary lights.

18
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Human and non-human primates

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Color matching experiments and physiological experiments show that most mammals are dichromatic, but most human and non-human primates are trichromatic.

19
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For example, if someone has only the L and M cones then when red and green pure wavelengths are added together, the perception is yellow–the same as for a pure yellow wavelength.

20
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The color circle (where is derived from color matching experiments) can be used to predict approximately when two lights will look the same, and what “color” will be seen when the lights are added together.

21
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For example, if a pure green wavelength and a pure yellowish-red wavelength are added together, the result is represented by a point along the line connecting them. If they are equal in intensity, the result will be at the midpoint (pink square). The result will look yellow. That same color can be produced by adding a bit of white to a pure yellow wavelength.

22
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Advanced slide for students who might be interested. n1 and n2 represent the spectral
distributions of two arbitrary lights. The distributions are a function of wavelength. The
triple line equal sign signifies that the two lights are perceptually indistinguishable. The
symbol c represents a number that scales the distributions up and down. Changing its value
is equivalent to raising and lower the intensity of the light without changing the shape of the
wavelength distribution.

23
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21
Another advanced slide that more accurately defines and explains trichromacy.
Trichromacy follows as long as the cone responses to the primaries are linearly
independent. Linear independence guarantees that there is a solution (c1, c2, c3) to
the three equations.

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22
Illustration of the distribution of the three types of cone photoreceptors in the human fovea.
A protanope has all L cones filled with the M cone pigment. A deuteranope has all M cones
filled with the L cone pigment. A tritanope has all S cones filled with L or M cone pigment.

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23
Demonstration of different forms of color vision deficiency. From Sharpe et al.

26
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24
Color (wavelength) discrimination in primates and humans. Macaques and humans
discriminate wavelengths well across the whole spectrum. Dichromatic primates
and humans have poor discrimination in the middle and long wavelengths.

27
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Color vision tests.

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26
How bad is normal color vision? Really bad. For example, a light consisting of two
pure wavelengths can look identical to one that has all wavelengths in equal
intensity. In hearing, this would be like confusing the sound of two pure tones with
the sound of white noise!

29
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Idea 1 is the classic idea that dates back in some form hundresds of years. Idea 2 is discussed in the recent literature. Idea 3 is probably the most important.

30
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Examples of natural daylight irradiance spectra plotted in relative log units.

31
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29
Example reflectance functions of fruit and leaves in the habitat of certain new world
monkeys.

32
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30
Examples from 300+ natural reflectance spectra of materials measured by Krinov
(1947). The general rule is that natural reflectance functions are fairly smooth and
natural light sources are fairly stereotypical. This can be demonstrated
quantitatively with mathematical/statistical analysis. The implication is that the
spectral distribution of a natural light can be estimated fairly accurately with just a
few types of cone. We do not have more types of cone because it would not add
much useful color information in the natural world.

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31
Color coding beyond the photoreceptors. Diagram of different bipolar and ganglion cell
types. Rodieck, R. W. (1998). The First Steps in Seeing. Sunderland, Sinauer.

34
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Receptive field types in the primate retina.

35
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Schematic of hypothesized color opponent mechanisms in the human visual system.
The hypothesis is that color is represented in three different color channels that are
derived from the three types of receptors. There is a great deal of psychophysical
and physiological evidence for this type of coding in the human visual system. This
schematic also illustrates what subjective percepts the channels supposedly
represent.

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38
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36
Psychophysical evidence for opponent processing model of color vision. Suppose a
just detectable amount of red light produces the responses shown on the left for each
color mechanism. Similarly a just detectable amount of blue-green light produces
similar responses (but of opposite sign in the opponent channels). The prediction is
that adding the just detectable red and green lights together should be undetectable
because the responses in the red-green and yellow-blue mechanisms would be
cancelled out. (The total response would be 0.3 which is less than the 0.4 produced
by each light alone.) This kind of experiment (done by S. L. Guth) is very strong
evidence for opponent processing. Other earlier evidence was obtained in hue
cancellation experiments bu Hurvich and Jameson (see textbook).

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41
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39
Steve Shevell’s demonstration of the effect spatial interactions on perceived color.
It is one of many demonstrations showing that color perception is affected by the
spatial context color and form. These mechanisms probably play an important role
in “color constancy,” the ability of humans to judge the reflectance of a material
fairly accurately independent of the color of the illumination. Another mechanism
that contributes to the solution to illumination problem is separate light adaptation
in each type of photoreceptor (this is called von Kries adaptation).

42
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Detection

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The image of an object must move on the retina or it will disspear. Example: stabilized images, retinal vasculature.

43
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Grouping

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Image features that move togeher tend to be grouped togther (Common fate Gestalt Principle)

44
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Motion cues to distance. When fixating the horizon while translating in a car or train, the
nearer an object the faster it moves across the retina. When fixating a closer object while
translating, the further an object from the fixated object the faster it moves across the retina.

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46
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5
Optic flow is a key source of information for heading (which is the direction of ones own
motion). This figure illustrates the local motion vectors produced during translation toward
a point on the horizon indicated by the vertical line. The length of the line segment attached
to each dot shows the speed of the motion, the direction of the line shows the direction of
the motion. Each dot represents an arbitrary point on the ground plane.

47
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6
The upper figure shows optic flow similar to the example in the previous slide. The lower
figure shows the optic flow vectors when the person is fixating at a nearby point while
continuing to translate toward the point on the horizon. Notice that the flow pattern changes
a great deal. Humans still correctly interpret this flow pattern. The optic flow pattern when
approaching a nearby by surface (e.g., a wall) can be used to judge the time until contact
with the surface, even if the observer does not know how fast he/she is moving.

48
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Visual Latency

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Contrast

Luminance (Pulfrich Effect)

Spatial Frequency

Three factors that affect visual response latency

49
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Changes in response latency for 12 different neurons in primary visual cortex (V1) as a function of stimulus contrast. Response latency decreases an anverage of 20-30 ms as the contrast is increase. (Time shift = change in response latency).

50
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Luminance (light intensity) also affects latency. One demonstration of this is the Pulfrich
effect. A filter (which reduces luminance) causes a longer latency of neural response in the
left eye. Thus, the moving green bar can appear at location P in the left eye but at another
location in the right eye. The result is an effective disparity which causes the bar to appear
to be at location Q (a different depth). The bar appears to be at a greater distance than P
when motion is left to right.

51
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11
Reaction time as a function of target spatial frequency (Breitmeyer 1975). The higher the
spatial frequency the longer it takes to see the target and hence the longer to push a button.

52
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Motion is extremly important to measure accurately. THe brain probably uses several different kinds of mechanism to measure motion.

53
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Schematic of simple delayed summation circuit for creating a direction selective simple
cell. A stimulus moving right to left will result in signals arriving at the summation site at
different times and so no spikes will be generated at the output. Note that delayed
multiplication would also work (in other words summation is not the only way of
combining responses that will work).

54
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14
On the other hand, a stimulus moving left to right will result in signals arriving at the
summation site simultaneously and so spikes will be generated at the output.

55
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Space-time plot of a movit vertical box.

56
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Top-down view (x-t) of the space time plots of a moving bar. Motion receptive fields are oriented in space-time.

57
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Robert Adams described the waterfall illusion after visiting this waterfall in 1834
(Aristotle, 384-322 BCE, noted this effect). This effect is predicted by adaptation of
direction selective neurons in the visual cortex.
To explain other motion mechanisms we need to talk about a couple of
computational problems that arise in motion perception.

58
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The correspondence problem in motion perception becomes most obvious in the case of
“apparent motion”, a phenomena exploited to create movies. This is not a very common
problem under natural viewing conditions.

59
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19
When a moving object is viewed through a small aperture (such as the small region that a
V1 receptive field covers) there can be considerable confusion about the actual direction of
motion. This is the “aperture” problem. This is much more common problem even under
natural conditions.

60
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Feature tracting

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20
Feature tracking (recognizing a complex feature or object and tracking it over time)
is one way of solving the aperture problem. It is probably only used by the brain for
slow speeds.

61
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Motion Blur

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When objects move they perceptually blur in the direction of the motion. This can
be used to obtain information about the direction of motion.

62
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The visual system averages/sums light over short periods of time. This causes a moving
stimulus to look blurred. A common example is twirling a sparkler. If a feature moves fast
enough the blur creates a spatial orientation in the direction of the motion. This could allow
orientation selective neurons in the brain to determine the direction of the motion. This is
the “motion streak” hypothesis.

63
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The middle temporal area (MT) is an area that appears to be specialized for motion
processing and is a cortical area where there is evidence that motion components are
combined to solve the aperture problem.

64
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A moving plaid experiment to measure motion coding of neurons in areas MT and/or V1. If
a neuron does not solve the aperture problem on expects the results on the left (component
response). If a neuron does solve the aperture problem one expects the results on the right
(pattern response).

A
65
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26
Responses of two different neurons to the moving plaid stimuli.

66
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27
Area MT is organized into direction of motion columns.

67
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Area MT in the macaque monkey corresponds to the are V5 (the medial temporal and
medial superior temporal areas) in the human brain.

68
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