Download Lecture - ClassTools.Info

Vision
• Photoreceptor cells
• Rod & Cone cells
• Bipolar Cells
• Connect in between
• Ganglion Cells
• Go to the brain
Vision
LGN
V1
V1
LGN
ganglion
cells
optic chiasm: where the
ganglion cells cross so the
left side of each eye goes
to the right side of the
brain, and vice versa.
The Eye
rod cells:
cone cells:
• periphery
• movement
• black and white
• fovea (center)
• detail
• color
500 nm light
blue green red
(broad tuning)
cone firing
The Eye
rod cells:
cone cells:
• periphery
• movement
• black and white
• fovea (center)
• detail
• color
blue green red
(broad tuning)
cone firing
The Eye
rod cells:
cone cells:
• periphery
• movement
• black and white
• fovea (center)
• detail
• color
bipolar & horizontal cells
b
b
b
b
h
h
h
h
h
h
The Eye
rod cells:
cone cells:
• periphery
• movement
• black and white
• fovea (center)
• detail
• color
bipolar & horizontal cells
• lateral inhibition
+
- - - - - - - + + + +
Lateral Inhibition
9
9
9
9
1
1
1
1
1
9
9
9
9
- 0
+
0
-
Lateral Inhibition
9
9
9
9
1
1
1
1
1
9
9
9
9
0
- 0
+ 4
-
Lateral Inhibition
9
9
9
9
1
1
1
1
1
9
9
9
9
0
0
- 4
+ -4
-
Lateral Inhibition
9
9
9
9
1
1
1
1
1
9
9
9
9
0
0
4
- -4
+ 0
-
Lateral Inhibition
9
9
9
9
1
1
1
1
1
9
9
9
9
0
0
4
-4
0
0
0
-4
4
- 0
+ 0
-
The Eye
rod cells:
cone cells:
• periphery
• movement
• black and white
• fovea (center)
• detail
• color
bipolar & horizontal cells
• lateral inhibition
• edge detection
ganglion cells
Bipolar cells
front view
The Eye
rod cells:
cone cells:
• periphery
• movement
• black and white
• fovea (center)
• detail
• color
bipolar & horizontal cells
receptive field
• lateral inhibition
• edge detection
ganglion cells
-
+
The Eye
rod cells:
cone cells:
• periphery
• movement
• black and white
• fovea (center)
• detail
• color
bipolar & horizontal cells
receptive field
• lateral inhibition
• edge detection
ganglion cells
• center/surround
-
+
Center-Surround
(Blob detector)
firing frequency
+
light position
time
Center-Surround
firing frequency
+
light position
time
Center-Surround
firing frequency
+
light position
time
Center-Surround
firing frequency
+
light position
time
Center-Surround
firing frequency
+
light position
time
Center-Surround
firing frequency
+
light position
time
Center-Surround
firing frequency
+
light position
time
Center-Surround
firing frequency
+
light position
time
Center-Surround
firing frequency
+
light position
time
Center-Surround
How’s it done?
Difference of Gaussians (Mexican hat)
light position
Distributed Visual Representation
• Different cells respond to different properties,
such as bars of light at different orientations
(i.e. the simple cells in V1).
• Different areas of the brain are dedicated to
processing form and location information
(i.e. the “what” and “where” systems, in
the temporal and parietal lobes, respectively)
How does your brain put it together again?
Binding Problem
•“red” neurons
•“blue” neurons
•“square” neurons
•“circle” neurons
•“upper-right”
•“lower-left”
How do we know which feature
goes with which object?
Binding Problem
•“red” neurons
•“blue” neurons
•“square” neurons
•“circle” neurons
•“upper-right”
•“lower-left”
How do we know which feature
goes with which object?
Binding Problem
•“red” neurons
•“blue” neurons
•“square” neurons
•“circle” neurons
•“upper-right”
•“lower-left”
How do we know which feature
goes with which object?
The Computations of Human Vision
Visual system must calculate
Object color (Mostly known)
Object shape
Begin with edges (Known)
Find blobs (Known)
How edges/blobs combine to form objects
(Mostly Unknown)
Object movement (Mostly known)
The Computational System of Vision
Object Motion
Marr’s levels:
Computational
Determine motion
Representation & Algorithm
Mostly known (but not by us!)
Physical Implementation
Neurons in the eye and brain
Hierarchical processing
High-level processing
Examples
Biological motion
Object motion
Optic flow
Low-level processing
Retinal motion
Hierarchical processing
High-level processing/High complexity
…
Superior Temporal Sulcus (STS)
Medial Superior Temporal area (MST)
Middle Temporal Area (MT/V5)
Primary visual cortex (V1)
Lateral Geniculate Nucleus (LGN)
Retina
•
•
•
•
Biological motion
Object motion
Optic flow
Retinal motion
Low-level processing/Low complexity
Limits of motion perception
We can’t perceive motion that is
either too FAST or too SLOW.
Vertical
position
Upward motion
time
Downward motion
Apparent Motion
• “Broken” motion
• Stimulus flashing at different positions
at different times
Flicker Rate
Very fast
Somewhat fast
Phi
Movement
Optimal
Beta
Movement
Very slow
Phi Movement/Motion
• A “pure sense” of motion without seeing
the intermediate steps
• No link-up/fill-in
Beta Movement/Motion
• Perceptually linking up the frames
• Smooth motion
• Motion picture technology
The Correspondence Problem
?
The Correspondence Problem
• How do we figure out which frame-2 dot
should match with each of the frame-1
dots?
Frame 1
Frame 2
?
The Wagon-wheel illusion
t1
Perceived direction
Real direction
Perception:
Reality:
Slow CW
Slow CW
Ambiguous
Medium CW
t2
Slow CCW
Fast CW
The Aperture Problem
• Following from the correspondence problem
• When the line’s motion is viewed through an
aperture, how do we figure out the “correct”
motion?
The Aperture Problem
• There are “infinitely many” possibilities.
…
or
or
…
•
The Aperture Problem: a
solution
It’s not a problem:
if the line has texture, or
if the line has endings, or
if the line is not straight, or…
…as long as there’s
a UNIQUE POINT!
The Barberpole Illusion
• Perceived motion direction is parallel to
the orientation of the rectangle
• Can be explained by “Unique-point
heuristic”
Perceived direction
– Unique points are assumed to be on the long
edge
Optic Flow
Optic Flow
• Background scene flows as our we move
• We process motion signals at different
locations to understand the optic flow
pattern
• Optic flow is useful
for inferring the
direction of
self-motion
Optic Flow
• Most studied flow patterns
Translational
- object movement, eye movement,
etc.
Rotational (or circular)
- head movement, eye movement, etc.
Radial (expansion/contraction)
- motion in depth, self-motion, etc.
– They can represent most of the optic flows
we see
– Computationally, rotational and radial flows
are more complex than translational ones
Retina Motion vs REAL Motion
• Motion constancy
– try tracking your moving finger!
• Retinal motion is combined with eyemovement to generate motion percepts
Motion in depth
• Retina is flat  Motion signals are only 2D
• How can we know when something is
moving towards/away from us?
• Try moving your finger towards your nose
Motion in depth
• The brain combines motion signals from
the two eyes to infer motion in depth
Left eye
Right eye
Far
Right eye: leftward
+) Left eye: rightward
Approaching
Right eye: rightward
+)
Left eye: leftward
Receding
Close
Biological Motion
• We are very sensitive to biological motion
• An analogy: Face in object perception
• Appears to require
– extremely complex computations
– a special motion processing mechanism
Motion Blindness
• Patient LM
– Certain brain areas damaged through stroke
– Almost all cognitive functions were intact
except for MOTION perception
– She reported
• What she saw when pouring coffee into a cup: appears frozen like a glacier,
does not perceive the fluid rising, often spills or overflows it
• “When I'm looking at the car first it seems far away, but then when I want to
cross the road suddenly the car is very near”
– YouTube: http://www.youtube.com/watch?v=B47Js1MtT4w
Title: Akinetopsia (4:01)
(a reproduced documentary for a class project)