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Computational Vision
CSCI 363, Fall 2012
Lecture 25
Biological Motion Processing
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Motion Processing in V1
In V1, some simple cells and complex cells are tuned to
direction of motion. I.e. they respond most strongly to motion
in a given direction and their response falls off as the motion
deviates from that direction.
Tuning for 180 deg
Firing
Rate
120o
180o 240o
Direction of Motion
Direction Tuning
Polar Plot
(tuning for 180 deg)
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V1 neurons tuned to temporal
frequency
V1 neurons appear to be tuned to temporal frequency.
Their preferred speed depends on the spatial frequency of the pattern.
v = wt/wx
Firing
Rate
Temporal Frequency
Neurons in V1 behave like motion energy filters.
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Motion Processing in MT
MT (The Middle Temporal Area) is thought to be important for
processing motion information.
Characteristics of MT neurons:
1) Cells tuned for direction of motion (more broadly tuned than
V1 cells.
2) Cells tuned for speed. (Some cells specifically tuned for
speed. Not dependent on spatial frequency).
3) Large receptive field sizes. (Some are 100x bigger than V1
receptive fields). They range from 1-2deg in diameter in the
foveal region and increase in the periphery.
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Speed Selectivity
McKee and Nakayama have shown that people are very good at
discriminating two different speeds independent of spatial
frequency.
The Weber fraction gives a measure of how big a change in speed
is necessary to distinguish two different speeds. It is fairly
constant over a broad range of speeds:
DV/V = .05
MT may be the area that first computes speed independent of
spatial frequency.
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Direction Selectivity
V1 cells are sensitive to the direction of motion of the spatial
frequency components of a stimulus.
For example, in plaid stimuli a V1 cell will respond when
either sine wave is moving in its preferred direction, but will
not respond for the pattern motion in its preferred direction.
Some MT cells respond to pattern motion. They respond best
when the pattern motion of a plaid is in their preferred
direction.
20% of MT cells respond to the pattern motion. 40% respond
to component motion. 40% are in between.
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Responses to Plaids
Moving plaid:
+
=
Response to pattern
motion
MT response
V1 response
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(20% of cells)
Motion opponency
Psychophysical results suggest that neurons in the brain use a
motion-opponent processing (e.g. left - right).
Evidence:
1) We cannot see both left and right motion at the same time.
2) Motion after-effect: If you adapt to rightward motion, and
then look away at static image, you see leftward motion
MT cells appear to exhibit motion-opponency in their receptive
fields:
+
This has implications for motion transparency.
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MT cells have inhibitory
surround
-
Many MT cells have an inhibitory surround.
+
Motion in the surround inhibits the response to
motion in the center.
The inhibitory surround may be involved in:
• Figure-ground segmentation based on motion.
• Motion parallax
• Heading judgments.
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Evidence that MT processes
motion
1. Cells in MT prefer moving stimuli to static stimuli.
2. Lesions of MT cause loss of ability to discriminate motion
direction:
Newsome et al. performed an experiment to test this in monkeys.
Stimulus: Moving dots--Some percentage move in a coherent
direction (correlated dots), the rest move in random directions
(noise)
Task: Judge direction of motion (e.g. up vs. down).
Measure: Percent correlation needed to discriminate the directions
of motion.
Result: After lesion of MT, monkeys require a greater percentage
of correlated dots to make the discrimination (i.e. they were
worse at the motion task).
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Microstimulation experiments
Another piece of evidence for MT being involved in motion comes
from experiments in which MT cells are electrically stimulated
with a micro-electrode (microstimulation).
Salzman & Newsome (1994) showed that they could influence a
monkey's perception of motion by stimulation of cells in MT.
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2D Motion is just the Beginning
2D image motion contains information about:
• Relative depth of surfaces
• 3D motion of objects
• 3D structure of objects
• Direction of observer motion
Among other things.
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Structure From Motion
Structure from motion originally studied rigorously by Wallach and
O'Connell (1953).
They studied wire-frame objects and examined peoples ability to
judge the structure of the objects when moving.
The ability to see a 3D structure from a moving 2D image is known
as the Kinetic Depth Effect.
Demo: http://www.michaelbach.de/ot/mot_ske/index.html
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Inherent Ambiguity
How do we compute a 3D motion from a 2D image motion?
Given the 2D image motion, there are multiple possible 3D
motions that could have generated it:
?
Image
plane
v
To solve for 3D motion from 2D image information, we must
use a constraint.
The Rigidity constraint assumes that the object is rigid.
Next time: Incremental rigidity scheme.
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