Ch 4 - Recognition Flashcards

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0
Q

Knowledge of where our limbs are relative to each other

A

Proprioception

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1
Q

Knowledge of where our limbs are

A

Kinesthesis

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2
Q

Information from touch

A

Haptic information

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3
Q

Ppl use exploratory procedures if trying to identify things by touch

A

Lederman and klatzky

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4
Q

Simplest form of 2D object recognition

A

Template matching

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5
Q

Second simplest form of 2D object recognition (and example)

A

Feature recognition ; pandemonium

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6
Q

What is needed for 2D object recognition to work

A

Structural descriptions

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7
Q

Marr: object is represented in simplified framework that is broadly the same shape as the object. What’s it called?

A

Canonical coordinate frame

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8
Q

The building blocks of Marr’s simplified representations

A

Generalised cones

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9
Q

The first step in creating representation of an object?

A

Finding a central axis

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10
Q

What has to be done to the object image to get the central axis

A

Use contour generator to find occluding contours (I.e.silhouette)

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11
Q

Marr’s name for a silhouette

A

Occluding contours

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12
Q

(Marr ) Silhouette isn’t enough on its own for definite identification, so the way we perceive it is constrained in 3 ways. What are they?

A

1) each pt on contour generator is a diff pt on the object
2) 2 points that are close on the generator are close on the object
3) all points on the contour generator are on a plane

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13
Q

What’s the problem with the assumption that all points on the contour generator are on a plane?

A

It would mean that, on a silhouette of a cube, it would look like very different points were on a plane together ( as the silhouette would be a hexagon)
, but this shape is not actually confusing for us

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14
Q

Marr n Nishihara: how do we break up the occluding contours into component parts?

A

Areas of sharp concavity

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15
Q

Marr and Nishihara: what are the component parts of contour generator?

A

Primitives

16
Q

Marr’s word for how the generalised cones are related to each other

A

Structural descriptions

17
Q

Biederman’s object components

A

Geons

18
Q

Geons

A

36 volumetric shapes

19
Q

What Biederman reckons gives critical cues to the relationship between geons

A

Non-accidental properties

20
Q

Eg of two of Biederman’s non-accidental properties

A

Straight edges, right angles (corners)

21
Q

Evidence for Biederman

A

Biederman (1987): people were v bad at identifying object when non-accidental properties were disrupted, eg. Deleted

22
Q

Evidence against Biederman

A

There is no evidence relating to the 36 geons or how structural descriptions specify relationships between them.

23
Q

Name of the model of face recognition

A

Bruce and Young model

24
Q

Name of face recognition computer model

A

IAC (interactive activation and competition) model

25
Q

The two face recognition problems that dissociate, suggesting that emotional response follows a different path from head-knowledge

A

Capgrass syndrome vs prosopagnosia

26
Q

Evidence that face recognition is a version of expert recognition

A

Inversion effect is also found for dog experts

27
Q

Area of brain that may be specific to face-processing

A

Area in the fusiform gyrus. (Tho some argue this area also responds when people discriminate between other objects of expertise)

28
Q

Evidence that axis location might play a key role in generating 3D descriptions x2

A

Warrington n Taylor (1978)

Humphreys n Riddoch (1984)