David Marr - Computational Investigation Flashcards

Computationalism

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1
Q

Bela Julesz: Random-dot stereogram

A

Julesz developed a method for creating depth perception in images using random-dot patterns, contributing to understanding visual perception.

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2
Q

Gestalt psychology

A

Focuses on how humans perceive the whole of something based on its parts, influencing the understanding of visual perception.

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3
Q

Mental rotation (Shepard and Metzler)

A

Demonstrated that mental rotation tasks involve mental imagery and that the time taken to mentally rotate an object correlates with its degree of rotation.

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4
Q

Neurons according to Barlow

A

Barlow’s definition emphasizes the functional understanding of neurons in transmitting and responding to signals, crucial for understanding brain function.

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5
Q

Rocha-Miranda and Bender (1972): Specialized neurons

A

Discovered specialized neurons for detecting complex objects like faces and hands, shedding light on neural processing of visual stimuli.

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6
Q

Waltz (1975)

A

Emphasized the computational challenge in interpreting human vision, proposing that analyzing physical arrangements of surfaces could aid in interpreting images.

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7
Q

Land and McCann (1971): Retinex theory

A

Introduced the Retinex theory, which explains color vision as a perceptual approximation to reflectance, influenced by surface properties like concavity or convexity.

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8
Q

Horn (1975): Shape perception

A

Explored shape perception from shading, illumination, and surface geometry, contributing to understanding visual processing.

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9
Q

Necker-cube illusion

A

Demonstrates perceptual ambiguity and the brain’s ability to interpret 3D structures, highlighting the complexity of visual perception.

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10
Q

Importance of computational theory

A

Emphasizes understanding the problem being solved over the mechanism used, crucial for comprehending complex systems like perception.

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11
Q

J.J. Gibson’s approach: Sense-data

A

Focuses on perception as extracting information from the environment, emphasizing the role of invariants in perception and critiquing reliance on sense-data alone.

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12
Q

Representational framework for vision

A

Addresses how vision selects relevant information from the environment, considering the purpose of vision in different animals.

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13
Q

Advanced vision

A

Studies lesions and their effects on object recognition and perception, highlighting the distinction between recognizing an object’s shape and understanding its use.

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14
Q

Marr’s framework of representational stages

A

Marr proposed a hierarchical model for understanding vision, emphasizing stages of representation from primal sketch to 3D models.

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