1 perceptual processes introduction pattern recognition pattern recognition top-down processing...

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1 Perceptual Processes Introduction Pattern Recognition Top-down Processing & Pattern Recognition Face Perception Attention Divided attention Selective attention Theories of attention

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Perceptual Processes

Introduction Pattern Recognition Top-down Processing & Pattern Recognition Face Perception

Attention Divided attention Selective attention Theories of attention

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Perception

Process that uses our previous knowledge to gather and interpret the stimuli that our senses register

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Pattern Recognition

The identification of a complex arrangement of sensory stimuli

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Patterns

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Theories of Pattern Recognition

Template Matching Theory

Prototype Models

Distinctive Features Model

Recognition by Components Model

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Template Matching Theory

Compare a new stimulus (e.g. ‘T’ or ‘5’) to a set of specific patterns stored in memory

Stored pattern most closely matching stimulus identifies it.

To work – must be single match

Used in machine recognition

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Examples of Template Matching Attempts

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Used in machine recognition

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Problems for Template Matching

Inefficient - large # of stored patterns

required

Extremely inflexible

Works only for isolated letters and simple

objects

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Prototype Theories

Store abstract, idealized patterns (or

prototypes) in memory

Summary - some aspects of stimulus

stored but not others

Matches need not be exact

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Examine the faces below, which belong to two different categories.

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Prototypes

Family resemblances (e.g. birds, faces,

etc.)

Evidence supporting prototypes

Problems - Vague; not a well-specified theory of pattern recognition

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Distinctive Features Models

Comparison of stimulus features to a stored list of features

Distinctive features differentiate one pattern from another

Can discriminate stimuli on the basis of a small # of characteristics – features

Assumption: feature identification possible

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Distinctive Features Models: Evidence

Consistent with physiological research

Psychological Evidence Gibson 1969 Neisser 1964 Waltz 1975 Pritchard 1961

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Can we empirically test the distinctive features theory?

• In other words, can we show that we must be processing features when we identify and distinguish one pattern from another – e.g. letters?

• There are many ways we can test a feature-based theory.

• For example:

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Scan for the letter ‘Z’ in the first column of letter strings.

Scan for the letter ‘Z’ in the second column of letter strings.

Where did you find the ‘Z’ faster: in column 1 or 2? What does this show?

Letter Detection Task

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Decide whether the pair of letters are the same or different: Yes or No

Letter Pairs

L T

T T

K M

G N

S T

G G

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T

ZA

How a Distinctive Features Model Might Work:

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Distinctive Features

Theory must specify how the features are combined/joined

These models deal most easily with fairly simple stimuli -- e.g. letters

Shapes in nature more complex -- e.g. dog, human, car, telephone, etc

What would the features here be?

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Recognition by Components Model

Irving Biederman (1987, 1990) Given view of object can be represented

as arrangement of basic 3-D shapes (geons)

Geons = derived features or higher level features

In general 3 geons usually sufficient to identify an object

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Examples of Geons

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Status of Recognition by Components Theory

Distinctive features theory for 3-D object

recognition

Some research consistent with the model;

some not

Recognition by Components Pro – Biederman found that obscuring vertices impairs object recognition while

obscuring other parts of objects has a lesser effect.

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Which is easiest to recognize as a cup? The left or right?

Con – Biederman – Not all natural objects can be decomposed into geons. What about a shoe?

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Support for Biederman

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Summary

Distinctive Features approach currently strongest theory

Perhaps all 3 approaches (distinctive features, prototypes, recognition by components) are correct

Regardless, pattern recognition is too rapid and efficient to be completely explained by these models

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Two types of Processing

Bottom-up or data-driven processing

Top-down or conceptually driven

processing

Theme 5 -- most tasks involve bottom-up

and top-down processing

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Thought Experiment

Assume each letter 5 feature detections involved

Page of text approximately 250-300 words of 5

letters per word on average

Each page: 5 x 5 x 250-300 = 6250 - 7500

feature detections

Typical reader 250 words/min reading

6250/60 secs =100 feature detections per

second

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Word Superiority Effect

We can identify a single letter more rapidly and more accurately when it appears in a word than when it appears in a non-word.

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Word Superiority- Non-word Trial

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Word Superiority: Word Trial

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Single Letter ‘K’ vs ‘K’ in a word

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Word Superiority: Single Letter Trial

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Word Superiority: Word Trial

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Altered Sentences in Warren and Warren (1970)

Sentence that was presented Word Heard

It was found that the *eel was on the axle

It was found that the *eel was on the shoe

It was found that the *eel was on the orange

It was found that the *eel was on the table

wheel

heel

peel

meal

*Denotes the replaced sound

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Attention

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Definitions of Attention

Concentration of mental resources

Allocation of mental resources

Multiple Aspect of Attention

• Divided attention

• Selective attention

• Theories of attention

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Divided Attention

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Reinitz & Colleagues (1974)

Divided Attention Condition

Subjects count the dots

Full Attention Condition

No instruction about dots

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Proportion of Responses that were “old” for Each of Two Study Conditions and Two Test Conditions

(Reinitz & Colleagues, 1994).

Study Condition

TestCondition

Full Attention Divided Attention

Old Face

ConjunctionFaces

.81

.48

.48

.42

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Divided Attention & Practice

Hirst, et. al. 1980

Spelke, 1976

Demo

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Upset

Hotel

Judge

Employment

Map

Indulge

Pencil

Problem

Key

Terrible

Can we always divide our attention with practice?

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Cell Phones & Driving – What Does the Research on Divided Attention Show?

• Is it safe to drive while talking on a cell phone?• Some states have passed legislation prohibiting

hand-held but not hands-free cell phones. Does this make any sense

• What about talking to someone in the car while driving versus talking on a cell phone?

• What are the chances of an accident?• Does practice make a difference? Why not?• Compare driving under the influence to cell phone

driving55

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Selective Attention

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Selective Attention (Dichotic Listening Task)

Shadowing

Irrelevant Channel

Cocktail Party Effect - Morray (1959)

Wood and Cowan (1995)

Treisman (1960)

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Dichotic Listening Task

T, 5, H

LEFT

T

5

H

RIGHT

S

3

G

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Cocktail Effect

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Treisman’s Shadowing Study

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Stroop Effect

Go to Stroop Demonstration

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Filter Models of Attention

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Capacity Model of Attention

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Cerebral Cortex & Attention

Stroop Effect Demos

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Experiment 1

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Read the Word.

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Green

Blue

Red

Purple

Green

Blue

Orange

Red

Blue

Green

Red

Blue

Orange

Green

Blue

Red

Purple

Orange

Green

Black

Stop!

Read the Word. Ignore the color

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Green

Blue

Red

Purple

Green

Blue

Orange

Red

Blue

Green

Red

Blue

Orange

Green

Blue

Red

Purple

Orange

Green

Black

Stop!

Experiment 2

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Name the Color of the Ink

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xxxxx

xxx

xxx

xxxxxx

xxxxx

xxxxx

xxxxxx

xxx

xxxx

xxxxx

xxx

xxxx

xxxxxx

xxxxx

xxxx

xxx

xxxxxx

xxxxxx

xxxxx

xxxxx

Stop!

Name the Color (e.g. Red say “blue”)

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Green

Blue

Red

Purple

Green

Blue

Orange

Red

Blue

Green

Red

Blue

Orange

Green

Blue

Red

Purple

Orange

Green

Black

Stop!

Stroop’s 3 Experiments• Exp 1 - Selectively attend to the verbal

aspect of the stimulus; ignore ink color

• Exp 2 – Selectively attend to the ink color of the stimulus; ignore verbal aspect

• Exp 3 – Why does ignoring the verbal aspect of the stimulus interfere strongly with color naming; but not the reverse?

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