chapter three Flashcards

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
bayesian inference
- thomas bayes - proposed that estimating the probability of an outcome is based on prior probability and likelihood
25
mirror neurons
neurons in the premotor cortex that respond when: - carrying out an action oneself - observing others carry out the same action - help understand intention
26
gestalt's laws of organization: good continuation
- points that when connected, create a smooth or straight line BELONG together - rope example
27
gestalt's laws of organization: pragnanz
- 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
gestalt's laws of organization: similarity
similar items appear to be part of the same group
29
physical regularities
- regular occurring physical properties - oblique effect, uniform connectedness, homogenous colours, light-from-above heuristic
30
oblique effect
easier to perceive horizontals and verticals than other orentations because of their frequent representation in our environment
31
uniform connectedness
objects defined by areas of uniform texture or colour
32
homogenous colours
within objects, same color
33
light-from-above heuristic
light in the natural world is assumed to come from above us
34
prior probability
initial belief about the probability of an outcome
35
likelihood
extent that evidence is consistent with the outcome