Psy 260 Announcements

Psy 260 Announcements

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

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

Cond. 1: Cond. 2: Cond. 3:

WORD ORWD D

XXXXX XXXXX XXXXX

Test: Which one did you see?

K K K

D D D

Word superiority effect, revisited

Word superiority effect, revisited

Word level

Letter level

Feature level

Input

See Reed, p. 36

Word superiority effect: An interactive activation model

WORK

K

| / \

Input: K or WORK or ORWDSee Reed, p. 36

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:

Word superiority effect Lowercase text is read faster than uppercase. Proofreading errors tend to be consistent

with word shape.

Evidence for word shape model:

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

Feature theories

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: 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??? Ski jump nose Jowly face Curly-textured hair Receding bays in hairline Boxy chin (David Perkins, 1975)

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

A B C

D E F

Contraindicated features: Worse than missing features (Perkins, 1975)

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.)

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.

A structure theory: RBC (Biederman)

Recognition by Components Geons: simple volumes (~35 of them) Construct objects by combining geons

RBC Theory

Analyze an object into geons Determine relations among the geons The relation among geons is critical!

RBC Theory

It’s hard to recognize an object without the information about relations among geons.

Hard!

RBC Theory

It’s hard to recognize an object without the information about relations among geons.

Easier!

RBC Theory

Basic properties of Geons View invariance Discriminability Resistance to visual noise

RBC Theory - Problems

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 Bar codes (by machines)

Feature Letter learning & confusions

Structural Biederman’s data (geons)

Prototype

Face recognition (Piecemeal or holistic?)

(A “special” case of pattern recognition?)

We see faces everywhere.

Image from

Mars’ surface

by Viking Orbiter 1

(Mcneill, 1998, p. 5)

Are faces “special”?

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

Are faces “special”?

How many faces can you recognize? Gibson: Patterns are easier to encode

as faces than as writing

Faces vs. writing

Are faces “special”?

How many faces can you recognize? Gibson: Patterns are easier to encode

as faces than as writing Prosopagnosia

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?

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?

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?

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

Feature What is a facial “feature”?

Invariant vs. transient features

Structural

Prototype

Familiar vs. unfamiliar faces

“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.

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:

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:

“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?

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!

The Caricature Generator (Brennan, 1982)

The average (prototype) face

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Veridical (traced) drawing

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Veridical (traced) drawing

Ronald Reagan

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A prototype theory of face recognition

When drawings were recognized, caricatures were faster than veridical drawings, which were faster than “anti-caricatures.”

Average face 0 distortion Caricature

(Rhodes, Brennan, & Carey, 1987)

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are needed to see this picture.

QuickTime™ and aTIFF (LZW) decompressor

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50% Caricature

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Caricatures

&

Anti-Caricatures

For a face,maybe we encodethe difference froma prototype.

Face Space

What kind of theory accounts for face recognition?

Theory: Objection:

Template Different lighting, orientation, motion, hair, glasses, age

Feature What is a facial “feature”?Invariant vs. transient features

Structural Faces are highly similar tokenswith the same structure!

Prototype This works! (but maybe not for unfamiliar faces and not

for kids)

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 There is even prosopagnosia for things

other than faces!

Some sources

George Lovell’s slides from Roth & Brucehttp://www.face-rec.org/interesting-papers/Other/FaceRecognition.pdf

“Early processing in the recognition of faces”http://www.diss.fu-berlin.de/2003/35/Kap3.pdf

Harmon, L. D. (1973). The recognition of faces. Scientific American, 229(5), 71-82.