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Theories of vision

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Lecture 5 covers all theories connected to vision.

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  • March 14, 2023
  • 6
  • 2019/2020
  • Class notes
  • Dr laura boubert
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Cognitive Psychology |Lecture 5|22nd Oct


VISION
- Provides information about our environment
- One of our sense and window to outside world
- Turns meaningless 2D array of intensity into 3D dimensional, meaningful objects
(interpretation of low-level visual information)
SOME MAZING FACTS
- Interaction of low-level visual processes, high level visual processes and LTM
- Objects and background
- Movement
- Shape shifting


THEORIES OF VISUAL PERCEPTION
- Higher cognitive processes
- Top down: the flow from the brain/ high level processes towards the raw data, role
of knowledge, memory, expectations, increases speed of processing (constructivist
theories)
- Bottom up: the flow of raw data/physical input towards the brain, data driven (direct
perception theories)
DIRECT PERCEPTION |Gibson 1966,1979
- Bottom up theory
- The pattern of light which reaches the eye contains all the visual information from
the environment (an optic array)
- The optic array provides unambiguous/invariant information about the object in
space
- Limitation: can’t explain constancy, can’t explain optical illusions
CONSTRUCTIVTIVE THEORIES |Gregory 1972, 1980
- Top down theory
- Nearly exact opposite Gibson
- Perception is not a direct consequence of sensory input. It is the result of a ‘best
guess’ to identify the sensory input
 The same physical stimulus can be interpreted differently
 We use other cues in the situation to resolve ambiguities
 Perception is totally conceptually driven, or top-down: role of context
X non of the theories is 100% correct X

, NEISSER CYCLIC MODEL |1964’s
Cycle of: sensory cues from environment-top
down search for expected features-perceptual
model-bottom up analysis of sensory features
This model runs constantly


OBJECT RECOGNITION
- How do we recognize object? Whole object? Assembled parts? Edges or surfaces?
Textures? Prototypes?
Object recognition: THEORIES
1. Template matching models (viewer-centered, normalization stage and matching)
 Compare to templates in memory until a match is found
 Problem of imperfect matches
 Can’t account for flexibility of pattern recognition system
2. Feature analysis model (feature detection theory)
 Every object is made out of features
 Pandemonium theory:




3. Recognition by components (object-centered)




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