PSY280 - 5. Object Recognition Flashcards

1
Q

Spatial Rule

A

stimuli presented close together in space tend to be integrated
hear a sound + see something at same time - link it to single event
if at diff locations, don’t see it as single event

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2
Q

Temporal Rule

A

stimuli presented close together in time tend to be integrated
no integration when stimuli presented at vastly diff times
hear creak + door opens, doesn’t make sense unless simultaneous

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3
Q

Inverse effectiveness

A

effect of integration is more pronounced with weaker
stimuli
bigger enhancement of perception when dealing with degraded intensity

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4
Q

Multisensory Integration improves

A

detection
response times: faster to respond when presented in 2 modalities
accuracy: various judgements of stimulus when more than 1 presented

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5
Q

fundamental attributes

A

defer to vision for judgments about space, to hearing for judgments about time
to identify 2 objects - have to be separated in space
tend to assume auditory stimulus at the location of visual event

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6
Q

Middle vision

A

stage of processing that comes after basic features & before object recognition or scene
house recognition: mix of complex processes that allows us to recognize it
this is the object, other is the background

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7
Q

Where are the edges?

A

How can we tell that car & house separate objects?
How can we tell that snowman & house are separate objects?
How can we tell that the windows & the house are part of
the same object?

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8
Q

Where are the edges?

A

decide where 1 object ends + another 1 behind cell identifies lines
we identify objects because continuous + connected
connectedness can’t answer snowman because they’re connected
we know windows + house are same objects, yet they’re connected
some objects overlap

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9
Q

Connectedness won’t work

Connectedness isn’t even necessary

A

continuous edges aren’t necessary for our system to perceive edges
visual system fills in gap
we perceive more contrast than actually there

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10
Q

Even if connectedness did
work, what are the
important edges?

A

we tend to see objects in contexts

our visual system not challenge to find boundaries even if there are multiple edges

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11
Q

illusory contours

A

don’t even need edges to perceive segregation
contour that is perceived even though nothing changes from 1 side of the contour to the other
illusory contours perception without sensation

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12
Q

Structuralism

A

perceptions result from summation of many elementary sensations
Gestalt
wilhelm wudnt - complex objects/perceptions can be understood by analyzing components

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13
Q

Structuralism

A

components = elementary sensations
couldn’t explain illusory contours or apparent motion
elementary sensations of apparent motion that structuralism couldn’t explain

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14
Q

Structuralism

A

flashing stationary light moving on + off giving illusion of movement
more + more perceptual phenomenon that structuralism couldn’t explain

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15
Q

Gestalt

A

whole is different than sum of it’s parts
direct response to structuralism
heuristics used to guide interpretation of retinal image
sometimes >1 principle at work - difficult to predict which one is going to win all else being equal

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16
Q

Gestalt

A

Gestalt principles are like individuals with opinions
about how the information should be organized
under diff conditions, diff principles/rules might have diff opinions

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17
Q

Gestalt

A

discuss how to organize sensory input into coherent sensory experience
perception by committee - a consensus does quickly emerge that allows us to settle on a single interpretation of a visual scene

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18
Q

gestalt principles

A
  1. simplicity: assume simplest structure - simpler to see it as
  2. similarity: tend to group together stars + circles
  3. proximity: 3 groups of 2 lines
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19
Q

gestalt principles

A
  1. common fate: movement in the same direction

5. closure: things close shaped tend to be grouped together/close objects that are incomplete

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20
Q

gestalt principles

A
  1. familiarity: 45 means something to us - then we see us
  2. good continuation
  3. similarity: all orange dots, proximity: close together
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21
Q

gestalt principles: good continuation vs. similarity

A

When 2 principles operating, it’s hard to predict which one takes precedence.
general assumption that smooth lines belong together + lines tend to follow smoothest path
not strict rules, just heuristics
but if good continuation vs similarity pitted against each other, similarity wins

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22
Q

similarity has it’s limits

A

similarity has limits: works for colour, shape, size, orientation
but combo of these features doesn’t work too well

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23
Q

perception by committee

A

diff rules can come together + our perceptual experience isn’t always clear about which one wins
middle vision = specialists, diff in opinion about what sensory input might mean
how to organize info through committee

24
Q

Pandemonium Model

A

Despite the potential for disagreement, there are some basic committee rules - example of how to implement computer vision model
Image demons like scanners: get sensory info
passes to first level of analysis: feature demons like specific features - cheer when preferred feature is present

25
Pandemonium Model
cognitive demons like specific letters: listen to feature demons R cognitive demons making lots of noise, D demon + P demon is also making some noise Decision demon listen to cognitive demons to see which one is cheesing the loudest
26
Every image is, in theory, ambiguous
multiple interpretations every image is ambiguous but committee comes to consensus quickly using rules we can come to solution easily + rapidly house rules: honour physics + avoid accidents
27
RULE 1: honour physics
come to implicitly understand that objects occlude light assumption white square is occluding 4 discs behind it visual system know about this + other physical properties + use them to organize visual info
28
RULE 2: avoid accidents
could be generated by quadrilaterals at diff depths + angles, just standing at one place that sees this discards accidental viewpoints in consensus meeting so unlikely that perceptual system doesn’t even consider it
29
An accidental viewpoint
viewpoint relative to an object that results in | perception of an accidental or rarely encountered property
30
What is the figure & what is the (back)ground?
needs to parse everything to separate objects + background | earlier gestalt rules can help us separate, but can’t help us differentiate which is background + object
31
What is the figure & what is the (back)ground?
some specific Gestalt rules that just apply to figure-ground assignment (figure-ground segregation). process of determining that some regions of an image belong to figure (object) + other regions are part of the background
32
Border ownership
associated with the figure | face/vase figure - border ownership changes based on how you interpret the image
33
figure & ground
surroundedness: likely surrounded region is figure parallelism: contours parallel groups into a figure size: smaller figure as object, larger object as background
34
figure & ground
relative location: lower region is object symmetry: identify objects or features based on symmetry meaningfulness: objects that are meaningful to us tend to be identified as objects
35
naive template theory
visual system recognizes objects by matching neural | representation of image with a stored representation of same “shape” in the brain
36
naive template theory
matching pixels - templates involve an array of spot detectors if stimulus falls on filled spot detectors, match template too many templates to be involved
37
recognition by components
structural description of an object in terms of nature of its constituent parts & the relationships between those parts
38
recognition by components
parallel contours: lines always parallel to each other | exploits the concept of non-accidental properties: an edge feature that is not dependent on exact viewpoint.
39
recognition by components
always able to detect edge feature no matter what orientation except for 1 viewpoint: coin curves except when dead on
40
recognition by components
t-junctions (occlusion): occur when 1 surface occludes another y- & arrow junctions (corners): signal corners
41
Geons
geometric ions - basic units of objects 36 geons, each composed of unique set of NAPs elements that involve structure descriptions combined non accidental properties in novel ways to represent 37 unique geons recognizable from any viewpoint
42
Geons
``` viewpoint-invariance: can be identified when viewed from most viewpoints nonaccidental properties (edges) axis straight or curved: skewer on constant/expanded: parallel? ```
43
Principle of componential recovery
If we can see the geons, we can identify the object too many of nonaccidental properties are obscured meaning you can’t identify geons if you move a little bit, you can identify it need access to nonaccidental properties, to get geons, to get object
44
Geons
only need to see a few geons to identify an object give them 3/9 78%, 6/9 90% flexible templates
45
recognition is sometimes holistic
recognition is not completely viewpoint invariant. experts on identifying greebles would do poorly if upside down but rbc does get us far in object recognition
46
contextual modulation
evidence of Gestalt rules in the brain, both through neuroimaging & at the level of the neuron contextual modulation: change based on context
47
contextual modulation
neuron’s response is influenced by stimulation outside it’s receptive field same stimulus in diff contexts providing context of good continuation - neuron likes it more + is more active
48
contextual modulation: good continuation
likes a continuous line outside its receptive field | changing response based on stimulation outside receptive field
49
contextual modulation: figure-ground segmentation
neuron recognizes figure ground, top: bar is in object, more response bottom: bar is in background, less response
50
neural activity correlates with sensory experience
different sensory input different neural activity hard to tell if cat sees them as separate stimulus
51
does neural activity correlates with perceptual experience?
You have to be able to keep the sensory information identical, but somehow generate different perceptual experiences.
52
does neural activity correlates with perceptual experience?
have to make task really difficult show them image in peripheral vision perception outlasts sensory stimulation once removed still capable of receiving info unless you mask it by presenting another stimulus
53
does neural activity correlates with perceptual experience?
yes: All of these curves represent responses to the presentation of Harrison Ford’s face. had to identify what they saw: harrison ford, a diff face, or diff picture
54
does neural activity correlates with perceptual experience?
correct identification, face but incorrect identification face but did not see face: all cases harrison ford was stimulus fmri signal is huge when correct identification identification is baseline when saw pattern middle when saw face
55
binocular rivalry
You can also force 2 experiences with the same stimuli 1 image to 1 eye, other image to another eye: back + forth because of rivalry at fairly regular intervals - without permission
56
does neural activity correlates with perceptual experience?
same sensory input diff perceptual experience + diff neural signature green face over red house face comes in left eye, house on right eye switches back + forth
57
does neural activity correlates with perceptual experience?
identify when they see house + when they see face by pressing button fmri activity greater activation in ffa when seeing face, when house greater ppa activation than ffa ppa when house + ffa when face