chapter three Flashcards

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1
Q

perception

A

an interpretation of the sensory input

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2
Q

template-matching theory

A
  • a template of a visual is stored in memory
  • the presentation of a visual stimulus is compared with templates stored in memory (ie. fonts and seeing the same letter)
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3
Q

problems with the template-matching theory

A
  • the way we see things is highly variable
  • requires a huge number of templates, even for a single type of object
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4
Q

feature-detection theory

A
  • objects can be decomposed into parts (features)
  • features re matched to the features of objects stored in memory
  • feature overlap between the stimulus and item in memory leads to recognition (ie. knowing that something is a chair because it has 4 legs and a base to sit on)
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5
Q

niesser’s study

A
  • hypothesis: if recognition involves feature detection, there should be perceptual confusions (recognition should be hard of objects that share overlapping features)
  • results showed slower to detect letter “Z” among items (letters) with similar features (list 2 had letters with angular features), compared to dissimilar features (list 1 had letters with curved features)
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6
Q

distinctive features

A

features that help discriminate between two patterns (i.e. the bottom line in letter E distinguishing it from letter F)

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7
Q

problems with the feature-detection theory

A
  • does not take spatial relationships into account
  • detecting individual features can be inadequate for recognizing some patterns
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8
Q

structural theory

A
  • biederman’s recognition by components model
  • involves features and the arrangements of features
  • all objects are constructed from a small number of 3-dimensional shapes referred to as GEONS
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9
Q

problems with the structural theory

A
  • relying on features and how they combine is not enough to explain how we can distinguish specific members of a category
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10
Q

characteristics of perception

A
  • modifiable: can change with experience
  • results from reasoning process: knowledge, memory and experience influences perception
  • reciprocal relationship between perception and action
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11
Q

bottom-up processing

A
  • process of building a whole image from a set of features
  • happens simultaneously with top-down processing
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12
Q

top-down processing

A
  • built on prior knowledge and expectations that influence perception and pattern recognition
  • happens when bottom-up information is ambiguous
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13
Q

word superiority experiment

A
  • we are better able to recognize a letter if it is embedded in a familiar word
  • results of the experiment: greater accuracy recognizing a letter presented rapidly when it is part of a familiar word vs than presented alone or as a non-word
  • remember class experiment flashing x’s and letters in words
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14
Q

perceiving machines have difficulty with… (4 things)

A
  • solving the inverse projection problem
  • recognizing hidden or blurred objects
  • achieving viewpoint invariance
  • recognizing scenes
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15
Q

solving the inverse projection problem

A
  • when there is the same image on the retina from various objects, how you determine what that object is
  • remember two different sized square sticky notes and flashlight shadow example in class
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16
Q

recognizing hidden or blurred objects

A
  • when objects are obscured or blurred, computers have difficulty with recognition
17
Q

achieving viewpoint invariance

A

computers have difficulty with recognizing the same object from different viewpoints

18
Q

recognizing scenes

A

computers have difficulty perceiving a scene (real-world environment with items that are meaningfully organized with each other in context with the setting)

19
Q

transitional probabilities

A
  • the likelihood that one sound follows another sound (based on our knowledge of that language)
  • refer to “pretty baby” example
19
Q

speech segmentation

A

the ability to know when one word ends and another word starts in a conversation

20
Q

theory of unconscious inference

A

helmholtz proposed that the images on the retina are ambiguous and that some perceptions are from unconscious assumptions that occur rapidly

21
Q

gestalt laws of organization

A
  • good continuation
  • pragnanz
  • similarity
22
Q

regularities in the environment

A
  • characteristics in the environment that frequently occur; physical and semantic regularities
23
Q

semantic regularities

A
  • regularly occurring functions within a scene that give the scene meaning
  • scene schemas: knowledge of what is usually in a particular setting
24
Q

bayesian inference

A
  • thomas bayes
  • proposed that estimating the probability of an outcome is based on prior probability and likelihood
25
Q

mirror neurons

A

neurons in the premotor cortex that respond when:
- carrying out an action oneself
- observing others carry out the same action
- help understand intention

26
Q

gestalt’s laws of organization: good continuation

A
  • points that when connected, create a smooth or straight line BELONG together
  • rope example
27
Q

gestalt’s laws of organization: pragnanz

A
  • law holds that when you’re presented with a set of complex objects, your brain will make them appear as simple as possible
  • olympic circles example
28
Q

gestalt’s laws of organization: similarity

A

similar items appear to be part of the same group

29
Q

physical regularities

A
  • regular occurring physical properties
  • oblique effect, uniform connectedness, homogenous colours, light-from-above heuristic
30
Q

oblique effect

A

easier to perceive horizontals and verticals than other orentations because of their frequent representation in our environment

31
Q

uniform connectedness

A

objects defined by areas of uniform texture or colour

32
Q

homogenous colours

A

within objects, same color

33
Q

light-from-above heuristic

A

light in the natural world is assumed to come from above us

34
Q

prior probability

A

initial belief about the probability of an outcome

35
Q

likelihood

A

extent that evidence is consistent with the outcome