Object and face perception Flashcards

1
Q

What is object and face perception

A
  • This is where we look at objects (everything) and change this to meaningful information
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2
Q

Detection and recognition

A
  • Our brain forms groups of objects based on sounds
  • Our brain can recognise that something is there and then uses our memory to decide what is it
  • Colour and orientation and spatial frequency also help with feature detection
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3
Q

What is grouping

A
  • Our brain is able to automatically sort features.
    For example, proximity, similarity and closure
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4
Q

What happens at a luminance boundary

A
  • Excitation and inhibition cancel each other out when luminance is equal.
  • However, at the luminance boundary, there is no balance which means that perceived brightness is increased
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5
Q

Contours for visual objects

A
  • Different neurons respond to different frequencies (high and low) for example, Mona-Lisa
  • Vital for turning 2D objects into 3D objects
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6
Q

Shape from shading

A
  • Shading shows texture and depth which helps to identify 3D objects
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7
Q

The role of expectation

A
  • What we expect to see influences what we do see
  • ‘built in expectations’
  • Everyone has different experiences and expectations
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8
Q

Face detection

A
  • First step is to detect a face this means we have to look at different features of the face that are common across all faces
  • Template matching is a simple example of detection
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9
Q

Face recognition

A
  • After detection of a face, features are analysed to categorise
  • For example, different facial expressions help to see the emotion
  • Also can identify who it is

Challenges of face recognition:
- There are factors which impact what we see; lighting, different context

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10
Q

Are faces special

A
  • Newborns can detect face of their mother
  • we have tendencies to see faces in objects
  • Pareidolia, we imagine there are faces when there aren’t for example in stones or leaves
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11
Q

Evidence for innate ability

A
  • New born studies which look at preferential looking
  • New borns look longer at features which are arranges as a face rather than jumbled features.
    Johnsen et al (1991)
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12
Q

Face inversion task (Yin, 1969)

A
  • Better at recognising faces the right way up rather than upside down.
  • Much more significant for faces than anything else.
    i.e. context is important
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13
Q

Negative Contrast faces (Kemp et al, 1990)

A
  • Harder to recognise when pattern of light and dark changes
  • Easier to recognise when pattern of colouring is what we are used to seeing.
    i.e. context is important
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14
Q

Hollow Face illusion

A
  • Like as mask you would wear
  • Painted inside of the mask (indent side) in a way you would paint a face, makes it seem as though the face is popping out at you
  • Painting the face to look as though light is hitting it the way you’d expect although works without highlights.
  • Blurred lines between perception and cognition as cognitively you know it’s a mask but you can’t override the 3D affect
  • Shapes and shading is a bit ambiguous if you don’t know where the light sauce is coming from
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15
Q

The affect of inversion on the Hollow Face and the Hollow Potato illusions (Hill and Bruce, 1994)

A
  • Made a potato hollow
  • Measure how close people had to get to the object until they see it not as convex (popping out) rather than concave (dimple)
  • The closer you are, the illusion went away, potato
  • You would have to get closer for the face illusion
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16
Q

Do we process faces in a particular way

A
  • The idea that faces are convex overrides knowledge
  • Potato illusion shows that we have that same expectation for all objects not just faces
  • However, illusion is stronger for faces
17
Q

Face recognition is different to object recognition Moscovitch et al.1997

A
  • Patient CK finds it hard to recognise objects although they do not find it hard to recognise faces
18
Q

Prosopagnosia
Meadows, 1974; Damasio et al. 1982

A
  • inability to recognise certain faces
  • Although their object recognise is absolutely fine
  • Damage to Temporal areas rather than visual areas.
19
Q

Face specific areas
Perrett et al. (1979, 1982)

A
  • Cells in the superior temporal sulcus are selective for faces. (in monkeys)
  • They respond more to human faces than monkey faces
20
Q

Objected Centred vs Viewer Centred
Hasselmo et al (1989)

A
  • Some neurons respond to faces at different angles
  • Some respond to animations rather than photos (respond to eye gaze)
  • Object vs Viewer, some neurons only recognise from a particular angle but others can respond from any angle
  • Not viewer centred, doesn’t matter where we are to the object.
  • Memory is important as well as scocial attention
21
Q

Functional Imaging (fMRI)

A
  • Fusiform face area responds more to faces than other common objects
  • Haxby et al. 2000, should be looking at other things as well such as eye gaze and different angles may activate FFA differently
  • People who can’t recognise faces have damage to the fusiform area
22
Q

Features of Configuration

A
  • There are different features of the face i.e. nose, mouth, eye etc.
  • Humans are sensitive to how the face is arranged.
23
Q

Holistic Processing
Tanaka & Farah 1993

A

Comparison of faces and housing
- trying to recognise a nose and a front door on it’s own is hard
- if you put the front door on the house and the nose on the face it is more recognisable
- Although, still easier to recognise the face rather than the house

24
Q

Composite face effect

A
  • Two faces put together (bottom and top half diff)
  • Holistic processing is natural
  • Can’t recognise the face when bottom and top half are in one face but when split apart, it’s easier to recognise the face
25
Q

Thatcher Illusion

A
  • When the face is upside down, you can’t notice anything wrong with the image as we interpret each feature of the face separately.
  • When the face is then turned the correct way up, we can the odd features (the eyes and mouth are upside down)
  • Due to holistic processing when the image is upright we can see what is wrong with it.