Course Overview
Acquisition
(perception)
Knowledge
ch. 3: Vision. How are
objects recognized?
-It looks easy but it’s not
ch.4: Attention.
The Brain
Use
Object Recognition
• Visual System Recognizes:
– Object Identities (man, woman, child, oar, lake)
– Spatial Layout of Scene
– Properties of Surfaces(color, texture, etc.)
• Are these real psychological dimensions?
(What about Small vs. big? Alive vs. Inanimate?
Tool vs. Non-tool? soft vs. hard? )
• - Are these dimensions processed independently by the
mind/brain? (after all, our subjective experience is that of
an integrated scene)
Specific Disorders suggest functionally
independent types of visual analysis
1. Visual Agnosia:(object identity)
• loss of ability to recognize objects
• preserved ability to navigate, reach
• Bilateral damage to occipital/temporal
• Prosopagnosia (specific to face recognition)
2. Balint’s Syndrome:(spatial layout)
• inability to navigate, reach
• preserved ability to recognize objects
• damage to parietal areas
3. Cerebral Achromatopsia (color)
• inability to discriminate colors
•distinct from color blindness--Color blindness results
from abnormalities in the photoreceptors of the eye. But
cerebral achromatopsia results from damage to posterior
visual areas in the brain
fMRI studies have confirmed the anatomical
Segregation of these functions
1. Object recognition:(lateral occipital cortex)
•face recognition (medio-temporal)
2. spatial layout and spatial attention
•parietal areas
3. Color
• medio-temporal
What is difficult about object recognition?
1. The visual system must carry out “image segmentation”, but
object boundaries are not easily determined
3. Objects may occlude each other
or they may be superimposed on
each other.
2. Objects may appear anywhere on retina in any size
A A
A A
AA + A A
AA
A
A
A
A
A
Perhaps the brain is able to represent these objects in a way that is “translationally
invariant” and “size invariant”.
4. Same object category (‘e’) may have different shapes
E
E
E
4. Same object (‘this door’) may have different shapes
Perceptual constancy: Shape
The many shapes of Hillary…
QuickTi me™ and a
GIF decompressor
are needed to see t his pict ure.
5. Object may be abnormally oriented
Words: Moderate Effects
Letters & Digits: Small Effects
How is object recognition accomplished?
Simplest idea: “Template Model”:
Store in brain a copy of what every possible input will
look like.
Match observed object to the proper image in memory
Template Theory
Perceptual
Representation
Memory Representations
Problems with Template Theory:
(1) Massive numbers of templates are required (remember all those E’s?).
(2) Predicts no transfer to novel views of the same object
(unlikely for different retinal positions)
(3) Objects are often obstructed (remember the baby?)
Feature Analysis Theory
A fixed set of elementary properties are analyzed
Independently and in parallel across visual field.
Possible examples
Free line endings:
Line Orientations:
Different Sizes:
Curvature:
Colors:
+45deg. -10deg.
A Simple Version of Feature Theory
Perceptual
Representation
3 Horizontal lines
1 Vertical line
4 Right angles
E
F
Memory
Representation
3 Horizontal lines
1 Vertical line
4 Right angles
2 Horizontal lines
1 Vertical line
3 Right angles
Evidence that Features are really basic
elements of visual processing
• Physiological Evidence
– Individual neurons respond preferentially to different
kinds of simple visual features
• simple cells--respond best to lines or angles of a specific orientation
and retinal position
• complex cells--fire maximally to lines or angles without respect to
location. They often also have preference for stimuli moving in
certain directions…
• hypercomplex cells--fire maximally have even more complicated sets
of requirements for maximal firing. (e.g. corners, notches….etc.)
Adaptation Effects are indicators of
elementary visual features...
•Your eyes are always moving, even when “fixated”(microsaccades)
•An image completely still on the retina will slowly fade from view, because
• individual feature detectors become habituated (fatigued) with prolonged,
sustained stimulation.
•Retinal stabilization procedure allows direct demonstration of this
phenomenon.
More Evidence for Features...
In a Visual Search Task:
(1)Targets defined by a single feature are easy to
detect(the red item; the square)
(2) Targets defined by a combination of features are
difficult to detect (the red square).
Let’s try it out
Call out “now!” when
you see the horizontal line.
Typical Results for “Feature Search”
“No”
Reaction
Time
(msec)
“Yes”
2 4 6
10
20
30
# of items in display
These results suggests parallel analysis and detection of simple visual features.
Conjunction Search
When targets are defined by:
• Combination of features (e.g., red AND horizontal)
• Spatial arrangements of features (e.g. black above white)
Call out “Now!” when you find the black
square above the white square:
Treisman’s Results for
“Conjunction Search”
Reaction
Time
(msec)
“No”
“Yes”
2 4 6
10
20
30
# of items in display
When higher order analysis or integration of multiple features is required,
search is much harder, and reaction time rises with number of distractors.
Detecting absence of a feature
Look for circle missing the free line
ending
among
Detecting presence of a feature
Look for circle with the free line
ending
among
How do we make an object
out of a pile of features?
Word Recognition: A Case Study
• Frequency Effects
• Word Frequency: Frequent words are
recognized more easily
• Repetition Priming:Words seen
recently are perceived more easily
• Context Effects
• Word Superiority: Individual letters are
easiest to identify when they are part
of a word (work vs. orwk)
• Well-formedness: Individual letters are
recognized more easily as part of
“word-like” stimuli than in a random
strings of letters (lipe vs. lpei).
An item will appear
word
An letter will appear
k
Word superiority
WORD
D
Guess = 1/5 correct
____
_
WORD
WORK
WORM
WORE
WORN
Guess = 1/26
correct
WORD
RWOD
D
XXXX
K
XXXX
D
XXXX
K
XXXX
D
XXXX
K
XXXX
D
This “forced-choice” procedure controls for the effects of guessing, and confirms
the validity of the word superiority effect.
WORD
ZORD
D
XXXX
K
XXXX
D
XXXX
K
XXXX
D
XXXX
K
XXXX
D
Interactive Activation Model
explains the word superiority effect
• Letters in words benefit from bottom-up and
top-down activation
• But letters alone receive only bottom-up
activation.
WORD WORK
WORD
K
XXXX
D
D
K
features
D
K
XXXX
D
D
features
K
Spared slides
A simple “feature net” model of word recognition
TORQUE vs.
•baseline activation: in the absence of direct stimulation. This is sensitive to
recency and frequency of stimulation.
•activation level: how active is a particular detector at a given moment
•response threshold: how much excitatory input does a detector require
before it “fires” and sends excitatory input further downstream.
CQRN
CQRN
Interactive Activation Model (IAM):
(McClelland & Rumelhart)
Previous models posed a bottom-up flow of
information (from features to letters to words).
IAM also poses a top-down flows of information
In addition, detectors at the same level interact with
each other.
Another important aspect of this theory is the
presence of inhibitory connections between detectors
that are inconsistent with each other...
Interactive Activation Model
RAP
Interactive Activation Model
explains the word superiority effect
• Letters in words benefit from bottom-up and
top-down activation
• But letters alone receive only bottom-up
activation.
WORD WORK
WORD
K
XXXX
D
D
K
features
D
K
XXXX
D
D
features
K