Psy 260 Announcements
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All late CogLab Assignment #1’s due today
CogLab #2 (Attention) is due Thurs. 9/21 at
the beginning of class
Coglab booklets and disks--along with a
printer that usually works--are available for
use in the Psychology Resource Room (enter
through Psych B 120)
Quiz alert!
Neural network models
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Nodes - processing units used to abstractly
represent elements such as features, letters,
and words
Links, or connections between nodes
Activation - excitation or inhibition that
spreads from one node to another
Word superiority effect, revisited
Word superiority effect, revisited
Cond. 1:
WORD
XXXXX
Cond. 2:
ORWD
Cond. 3:
D
XXXXX
XXXXX
Test: Which one did you see?
K
K
D
D
K
D
Word superiority effect, revisited
Word level
Letter level
Feature level
See Reed, p. 36
Input
Word superiority effect:
An interactive activation model
WORK
K
| / \
See Reed, p. 36
Input: K or WORK or ORWD
Interactive Activation Model of the word
superiority effect (McClelland & Rumelhart, 1981)
Interactive Activation Model of the word
superiority effect (McClelland & Rumelhart, 1981)
(Email example of mangled text!!)
James Cattell, 1886: Word superiority effect
(Reicher, 1969; Cattell, 1886)
Subjects recognized flashed words more accurately
than flashed letters.
He proposed a word shape model.
Evidence for word shape model:
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Word superiority effect
Lowercase text is read faster than uppercase.
Proofreading errors tend to be consistent
with word shape.
Evidence for word shape model:
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Word superiority effect
Lowercase text is read faster than uppercase.
Proofreading errors tend to be consistent
with word shape.
It’S dIfFiCuLt To ReAd WoRdS iN
aLtErNaTiNg CaSe.
Perception and Pattern
Recognition III:
Faces
How do people recognize faces?
Consider these types of theories:
Template theories
 Feature theories
 Structure theories
 Prototype theories
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Feature theories
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Patterns are represented in memory by their
parts.
In perception, the parts are first recognized and
then assembled into a meaningful pattern.
Piecemeal (as opposed to holistic)
What are the distinctive features for
faces ?
Eyes, nose, mouth - NOT!
What are the distinctive features for
faces ?
Eyes, nose, mouth - NOT!
Revisit Eleanor Gibson’s criteria:
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Each feature should be present in some patterns and
absent in others
A feature should be invariant (unchanged) for all
instances of a particular pattern
Each pattern has a unique combination of features
The number of features should be fairly small
A set of features is evaluated by how well it can predict
perceptual confusions.
Who are these people?
Same or different?
Who are these people?
Same or different?
Inspiration: Caricatures
“More like the face than the face itself”
 What are the distinctive features of a
face - say, Richard Nixon’s???
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 Ski
jump nose
 Jowly face
 Curly-textured hair
 Receding bays in hairline
 Boxy chin
(David Perkins, 1975)
Contraindicated features: Worse than
missing features (Perkins, 1975)
A
D
B
C
E
F
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
Revisit: Problems w/ feature theories
How to determine the right set of
features?
 What about the relationships between
features?
 What if all the features are present in
the pattern, but scrambled?
Features theories predict: No problem!
(and that’s the problem.)
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Face recognition is holistic
(Tanaka & Farah, 1993)
Structure theories
Build on feature theories
 Patterns are represented in memory by
features AND by the relations between
them.
 Holistic
 The context of the pattern plays an
important role in pattern recognition.
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A structure theory: RBC (Biederman)
Recognition by Components
 Geons: simple volumes (~35 of them)
 Construct objects by combining geons
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RBC Theory
Analyze an object into geons
 Determine relations among the geons
 The relation among geons is critical!
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RBC Theory
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It’s hard to recognize an object without the
information about relations among geons.
Hard!
RBC Theory
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It’s hard to recognize an object without the
information about relations among geons.
Easier!
RBC Theory
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Basic properties of Geons
 View invariance
 Discriminability
 Resistance to visual noise
RBC Theory - Problems
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Explains how people distinguish categories of
objects (types) - like cups vs. briefcases. But
how do people distinguish individual objects
(tokens) that come from the same category
(like faces)??
Neurons are to tuned respond to much
smaller elements than those represented by
geons!
Recap so far:
Theory:
What it explains:
Template
Feature
Structural
Prototype
Bar codes (by machines)
Letter learning & confusions
Biederman’s data (geons)
Face recognition
(Piecemeal or holistic?)
(A “special” case of pattern
recognition?)
We see faces everywhere.
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Image from
Mars’ surface
by Viking Orbiter 1
(Mcneill, 1998, p. 5)
Are faces “special”?
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How many faces can you recognize?
Are faces “special”?
How many faces can you recognize?
 Gibson: Patterns are easier to encode
as faces than as writing
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Are faces “special”?
How many faces can you recognize?
 Gibson: Patterns are easier to encode
as faces than as writing
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Faces vs. writing
Are faces “special”?
How many faces can you recognize?
 Gibson: Patterns are easier to encode
as faces than as writing
 Prosopagnosia
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We don’t need much information to
recognize a familiar face.
Guess who?
We don’t need much information to
recognize a familiar face.
Guess who?
Why is face recognition so interesting?
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It’s important!
Faces are highly similar to one another.
Yet we’re really good at it: we can tell an
astounding number of faces apart.
Not all facial information is created equal.
Could machines ever do as well as people?
Or even better?
Are faces somehow “special”?
Why is face recognition so interesting?
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It’s important!
Faces are highly similar to one another.
Yet we’re really good at it: we can tell an
astounding number of faces apart.
Not all facial information is created equal.
Could machines ever do as well as people?
Or even better?
Are faces somehow “special”?
Faces are hard to recognize in
photographic negative
(Galper & Hochberg, 1971)
Faces are hard to recognize
upside down (Yin, 1969)
Faces are hard to recognize
upside down (Yin, 1969)
“Early processing in the recognition of faces”
http://www.diss.fu-berlin.de/2003/35/Kap4.pdf
Faces are hard to recognize
upside down (Yin, 1969)
“Early processing in the recognition of faces”
http://www.diss.fu-berlin.de/2003/35/Kap4.pdf
Margaret Thatcher effect
(Thomson, 1980)
Margaret Thatcher effect
(Thomson, 1980)
Why?
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The configural processing hypothesis:
When faces are inverted, the
relationships among features are
disturbed.
So we don’t notice the odd configuration
in the Thatcher illusion.
(Bartlett & Searcy, 1993)
Faces are hard to recognize
upside down (Yin, 1969)
“Early processing in the recognition of faces”
http://www.diss.fu-berlin.de/2003/35/Kap4.pdf
What kind of theory accounts for
face recognition?
Theory:
Objection:
Template
Different lighting, orientation,
motion, hair, glasses, age
What is a facial “feature”?
Invariant vs. transient features
Feature
Structural
Prototype
Familiar vs. unfamiliar faces
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“Attribute Checking Theory”
 A feature
theory
 For familiar faces, internal features seem
to be more important than outside features.
 For new faces, we pay more attention to
outside features (hair, face shape, etc.)
(Bradshaw & Wallace)
Familiar vs. unfamiliar faces
“Early processing in the recognition of faces”
http://www.diss.fu-berlin.de/2003/35/Kap3.pdf
Children recognize faces
differently than adults do.
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Children under 10 use transient
features to distinguish unfamiliar faces.
 Strangers
wearing the same hat seem
similar, and are confusable.
(Susan Carey)
What makes faces confusable?
(Harmon, 1973)
Application:
Face recognition by eyewitnesses
Problem:
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Identikit: piecemeal, featural
Photo methods: Introduce interference, bias
Lineup: when the perpetrator is not present,
20-40% of witnesses select someone anyway.
With photos and lineups, witnesses compare
the suspects and choose the most similar one
False convictions often have eyewitness
testimony as the strongest evidence in the
The right way to do a lineup:
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“Showup” - view suspects or pictures one at a
time, ideally only once
If multiple viewings, then view each one the
same number of times, always in random
order (avoid between-suspect comparisons)
The one showing the faces must be blind to
whom law enforcement believes suspect is
(Otherwise, impossible to avoid bias)
Then false IDs drop to 10%.
Mistaken identity!
What about a structural theory of
face recognition?
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Pro: The relationships between features are
very important.
Pro: We often fail to recognize a familiar face
when we see it out of context.
Con: A structural theory doesn’t explain how
we can distinguish so many highly similar,
individual tokens.
(Moving right along: A prototype theory
What is a caricature?
An exaggerated representation of a face
 More like a face than the face itself!
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The Caricature Generator (Brennan, 1982)
The average (prototype) face
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
Veridical (traced) drawing
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
Veridical (traced) drawing
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
Ronald Reagan
A prototype theory of face recognition
When drawings were recognized, caricatures were faster than veridical
drawings, which were faster than “anti-caricatures.”
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
Average face
0 distortion
Caricature
(Rhodes, Brennan, & Carey, 1987)
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
50% Caricature
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Caricatures
&
Anti-Caricatures
For a face,
maybe we encode
the difference from
a prototype.
Face Space
What kind of theory accounts for
face recognition?
Theory:
Objection:
Template
Different lighting, orientation,
motion, hair, glasses, age
What is a facial “feature”?
Invariant vs. transient features
Faces are highly similar tokens
with the same structure!
This works! (but maybe not for
unfamiliar faces and not for kids)
Feature
Structural
Prototype
Is face recognition “special”?
No!
 There are other classes of patterns for
which people can distinguish huge
numbers of individuals (tokens).
 Ornithologists
recognize individual birds
 New England Kennel Club judges
recognize individual dogs
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There is even prosopagnosia for things
other than faces!
Some sources
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George Lovell’s slides from Roth & Bruce
http://www.face-rec.org/interesting-papers/Other/FaceRecognition.pdf
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“Early processing in the recognition of faces”
http://www.diss.fu-berlin.de/2003/35/Kap3.pdf
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Harmon, L. D. (1973). The recognition of
faces. Scientific American, 229(5), 71-82.