Chapter 4- Perceiving and Recognizing Objects Flashcards

1
Q

What are cells in VI interested in?

A

The cells in VI are optimally stimulated by bars and gratings of different orientations.

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2
Q

Extrastriate Cortex

A

The region of cortex bordering the primary visual cortex and containing multiple areas involved in visual processing.

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3
Q

Border Ownership

A

When one object is in front of another there will be a visual border formed between the object and the background. That border is “owned” by the object. It is the edge of the object, not a property of the background.

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4
Q

What are the two main pathways from the extrastriate regions?

A

The two main pathways are the “what” and “where” pathways.

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5
Q

What does the “where” pathway do?

A

This pathway heads up into the parietal lobe. Visual areas in this pathway seem to be important for processing information relating to the location of objects in space and actions required to interact with them.

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6
Q

What does the “what” pathway do?

A

This pathway heads down into the temporal lobe and is known as the what pathway. This pathway appears to be the locus for the explicit acts of object recognition that are of particular importance in this chapter.

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7
Q

Lesion

A

In reference to neurophysiology, 1. (n) A region of damaged brain. 2. (v) To destroy a section of the brain.

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8
Q

Agnosia

A

A failure to recognize objects in spite of the ability to see them. Agnosia is typically due to brain damage.

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9
Q

Inferotemporal (IT) Cortex

A

Part of the cerebral cortex in the lower portion of the temporal lobe, important in object recognition.

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10
Q

What did they discover regarding cells in the IT cortex?

A

They discovered that they have receptive fields that could spread over half or more of the monkey’s field of view. Furthermore, the usual spots and lines didn’t work well at all, but the silhouette of a monkey hand worked fantastically for some cells.

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11
Q

Homologous Regions

A

Brain regions that appear to have the same function in different species.

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12
Q

Fusiform Face Area (FFA)

A

A region of extrastriate visual cortex in humans that is specifically and reliably activated by human faces.

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13
Q

Extrastriate Body Area (EBA)

A

A region of extrastriate visual cortex in humans that is specifically and reliably activated by images of the body other thana the face.

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14
Q

Parahippocampal Place Area (PPA)

A

A region of extrastriate visual cortex in humans that is specifically and reliably activated more by images of places than by other stimuli.

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15
Q

Visual World Form Area (VWFA)

A

A region of extrastriate visual cortex in humans that is specifically and reliably activated more by images of written words than by other stimuli.

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16
Q

Feedforward Process

A

A process that carries out a computation (e.g., object recognition) one neural step after another, without need for feedback from a later stage to an earlier stage.

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17
Q

Reverse-Hierarchy Theory

A

A theory that fast, feedforward processes can give you crude information about objects and scenes based on activity in high-level parts of the visual cortex. You become aware of details when activity flows back down the hierarchy of visual areas to lower-level areas where the detailed information is preserved.

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18
Q

Mid-Level (Or Middle) Vision

A

A loosely defined stage of visual processing that comes after basic features have been extracted from the image (low-level or early, vision) and before object recognition and scene understanding (high-level vision).

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19
Q

What is the goal of mid-level vision?

A

The goal is to organize the elements of a visual scene into groups that we can then recognize as objects.

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20
Q

Illusory Contours

A

A contour that is perceived even though nothing changes from one side of it to the other in an image.

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21
Q

Occlusion

A

The fact that we can recognize that one object may be occluding, or blocking, another in a visual stimulus.

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22
Q

Rules of Evidence

A

The tendency of the visual system to make inferential leaps.

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23
Q

Structuralism

A

In reference to perception, a school of thought that believed that complex objects or perceptions could be understood by analysis of the components.

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24
Q

Gestalt

A

In German, literally “form.” In reference to perception, a school of thought stressing that the perceptual whole can be greater than the apparent sum of the parts.

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25
Q

Gestalt Grouping Rules

A

A set of rules describing which elements in an image will appear to group together. The original list was assembled by members of the Gestalt school of thought.

26
Q

Good Continuation

A

A Gestalt grouping rule stating that two elements will tend to group together if they seem to lie on the same contour.

27
Q

Texture Segmentation

A

Carving an image into regions of common texture properties.

28
Q

Similarity

A

A Gestalt grouping rule stating that the tendency of two features to group together will increase as the similarity between them increases.

29
Q

Proximity

A

A Gestalt grouping rule stating that the tendency of two features to group together will increase as the distance between them decreases.

30
Q

Parallelism

A

A rule for figure-ground assignment stating that parallel contours are likely to belong to the same figure.

31
Q

Symmetry

A

A rule for figure-ground assignment stating that symmetrical regions are more likely to be seen as figure.

32
Q

Camoflage

A

To a great extent, this is the art of getting your features to group with the features of the environment so as to persuade an observer that your features do not form a perceptual group of their own.

33
Q

Ambiguous Figure

A

A visual stimulus that gives rise to two or more interpretations of its identify or structure.

34
Q

Necker Cube

A

An outline that is perceptually bi-stable. Unlike the situation with most stimuli, most interpretations continually battle for perceptual dominance.

35
Q

Accidental Viewpoint

A

A viewing position that produces some regularity in the visual image that is no present in the world (e.g., the sides of two independent objects lining up perfectly).

36
Q

Figure-Ground Assignment

A

The process of determining that some regions of an image belong to a foreground object (figure) and other regions are part of the background (ground).

37
Q

What are the principles for figure-ground?

A

1) Surroundness
2) Size
3) Symmetry
4) Parallelism
5) Relative Motion

38
Q

Relatability

A

The degree to which two line segments appear to be part of the same contour.

39
Q

Heuristic

A

A mental shortcut.

40
Q

Surroundness

A

A rule for figure-ground assignment stating that if one region is entirely surrounded by another, it is likely that the surrounded region is the figure.

41
Q

Size

A

The smaller region in an image is likely to be figure.

42
Q

Symmetry

A

A symmetrical region is more likely to be seen as figure.

43
Q

Parallelism

A

Regions with parallel contours are more likely to be seen as figure.

44
Q

Relative Motion

A

How surface details move relative to an edge can also determine which portion of a display is the foreground figure and which is the background.

45
Q

Nonaccidental Feature

A

A feature of an object that is not dependent on the exact (or accidental) viewing position of the observer.

46
Q

Y and Arrow-Junctions

A

Almost always correspond to corners and thus don’t signal occlusions.

47
Q

T Junctions

A

Almost always occur when one surface occludes another.

48
Q

Global Superiority Effect

A

The finding in various experiments that the properties of the whole object take precedence over the properties of parts of the object.

49
Q

Bayesian Approach

A

A way of formalizing the idea that our perception is a combination of the current stimulus and our knowledge about the conditions of the world- what is and is not likely to occur. This approach is stated mathematically as Bayes’ theorem: P(A/O)= P(A) x P(O/A)/P(O), which enables us to calculate the probability (P) that the world is in a particular state (A) given a particular observation (O).

50
Q

What are the two factors Bayesian Approach asks us to consider?

A

1) Before you look at anything, how likely is what you are proposing? This is known as prior probability.
2) How consistent is each hypothesis with observation.

51
Q

Subtraction Method

A

In functional magnetic imaging, comparison of brain activity measured in two conditions: one with and one without the involvement of the mental process of interest. The difference between the images for the two conditions may show regions of brain specifically activated by that mental process.

52
Q

Decoding

A

The process of determining the nature of a stimulus from the pattern of responses measured in the brain or, potentially, in an artificial system like a computer network. The stimulus could be a sensory stimulus or it could be an internal state (e.g., the contents of a dream).

53
Q

Pandemonium Model

A

An account of letter recognition. Selfridge used “demons” as metaphor for processes that we would discuss in neural terms today. Selfridge had an initial early-vision signal-processing stage. Next, features were extracted: orientation lines, curves, and so on. In his third step, a set of “cognitive demons” each looked for the features of one letter. Finally, the “decision demon” pooled information across all the third-layer demons and choose the loudest demon as the answer.

54
Q

Template

A

The internal representation of a stimulus that is used to recognize the stimulus in the world. Unlike its use in, for example, making a key, a mental template is not expected to actually look like the stimulus that it matches.

55
Q

Structural Description

A

A description of an object in terms of teh nature of its constituent parts and teh relationships between those parts.

56
Q

Recognition-by-Components Model

A

Biederman’s model of object recognition, which holds that objects are recognized by the identities and relationships of their component parts.

57
Q

Geon

A

In Biederman’s recognition-by-components model, any of the “geometric ions” out of which perceptual objects are built.

58
Q

Deep Neural Network (DNN)

A

A type of “machine learning” in artificial intelligence in which a computer is programmed to learn something (here object recognition). These are artificial neural networks that have a large number of layers of nodes with millions of connections. First the network is “trained” using input for which the answer is known (“that is a cow”). Subsequently, the network can provide answers form input that it has never seen before.

59
Q

Entry-Level Category

A

For an object, the label that comes to mind most quickly when we identify it (e.g., “bird”). At the subordinate level, the object might be more specifically named (e.g., “eagle”); at the superordinate level, it might be more generally named (e.g., “animal”).

60
Q

Holistic Processing

A

Processing based on analysis of the entire object or scene and not on adding together a set of smaller parts or features.

61
Q

Prosopagnosia

A

An inability to recognize faces.

62
Q

Congenital Prosopagnosia

A

A form of face blindness apparently present from birth, as opposed to acquired prosopagnosia, which would typically be the result of an injury to the nervous system.