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Cognition and Perception

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1 Cognition and Perception
This is not a pipe. “Just try stuffing tobacco in it!” – Rene Magritte, 1930 This is not a rose.

2 The myth of vision as a faithful record
Figure The myth of vision as a faithful record of light ·       Concentric circles or continuous spiral? ·       The pattern of light is of concentric circles ·       Human vision sees a continuous spiral ·       Concentric circles or continuous spiral? ·       The pattern of light is of concentric circles ·       Human vision sees a continuous spiral

3 The Myth of vision as a passive process
The Grand illusion of complete perception (1) Vision is not rich in detail the size of a thumbnail at arm’s length is all that gets processed (2) Attention is limited: the law of ONEs vision sees one object, one event, one location These two factors are illustrated by Impossible triangle Escher drawings Bistable images

4 Brains construct a well-behaved 3-D world so we cannot experience a world that is not. Here we see an ordinary triangle and building with normal corners and angles instead of the shocking reality. Why?

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9 · A perceptually ambiguous wire cube
·       How many different interpretations can you see? Figure 1.4. “Subjective” perceptions are not necessarily “arbitrary” perceptions ·       A perceptually ambiguous wire cube ·       How many different interpretations can you see? Go to:

10 Bi-stable Images

11 Bi-stable Images

12 Figure 1.5. “Subjective” perceptions are not necessarily “arbitrary” perceptions
·       Did you see all of these interpretations? Why not? ·       Humans bring shared assumptions to the vision project, that objects are generally convex, that straight lines in a picture represent straight edges in an object, and that three-edge junctions are generally right-angled corners. ·       Brains see two instead of all of these interpretations? Why not? ·       Humans bring shared assumptions to the vision project, (1) that objects are generally convex, (2) that straight lines in a picture represent straight edges in an object, and (3) that three-edge junctions are generally right-angled corners.

13 Movement Illusion

14 Cognition and Perception
The finished files are the result of years of scientific study combined with the experience of many years. The finished files are the result of years of scientific study combined with the experience of many years.

15 Gestalt The whole is greater than the sum of its parts
Law of Pragnanz (“good figure”): We perceive things in the way that is simplest to organize them into cohesive and constant objects.

16 Gestalt Laws Laws of Grouping 1. Proximity 2. Similarity
3. Common fate 4. Good continuation 5. Closure/ convexity 6. Common region 7. Connectedness 8. Parse regions at deep concavities

17 Gestalt Laws Laws of Figure-Ground Segregation
1. Convex region becomes figure 2. Smaller region becomes figure 3. Moving region becomes figure 4. Symmetric ("good") region becomes figure 5. Nearer region becomes figure (multiple depth cues apply)

18 Figure 1. A: Kanizsa figure. B: Tse’s volumetric worm
Figure 1. A: Kanizsa figure. B: Tse’s volumetric worm. C: Idesawa’s spiky sphere. D: Tse’s sea monster

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20 Common Fate

21 Gestalt Laws Laws of Grouping Closure/ convexity

22 Optic Flow

23 Demos Charlie Chaplin mask demo Visual Illusions
Visual Illusions Moving random dot stereogram Spinning silhouette Gestalt Illusions

24 Quizz Which one of the following statements is not true about Gestalt psychology. It deals with figure-ground segregation It deals with object recognition It explains receptive fields Some of the gestalt principles include: good continuation, common fate and similarity

25 Two Visual Systems What your hands see differs from what the eyes see
Ventral ‘What’ system Dorsal ‘Where/ How’ system Brain lesions Ventral lesions: patients cannot name telephone but mime using it Dorsal lesions: can name it, but reach in wrong direction for it Roelofs Effect

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32 Object Recognition

33 Object Recognition (Called Pattern Recognition in Book)
How do you solve problem of Object Constancy? How does the brain know the objects are the same despite change in perspective?

34 What letter are these, and how do you know?

35 Top-Down & Bottom-Up

36 Bottom-Up Processing Direct Perception theories
Perception comes from the stimuli in the environment Parts are identified, put together, and then recognition occurs

37 Gibson’s Direct Perception (Ecological model)
All the information needed to form a perception is available in the environment Perception is immediate and spontaneous Affordances and attunements Perception and action cannot be separated Action defines the meaningful parameters of perception and provides new ways of perceiving

38 Top-down Processing Constructive Perception theories
Top-down Processing Constructive Perception theories People actively construct perceptions using information based on expectations Top down processing Perception is not automatic from raw stimuli Processing is needed to build perception Top down processing occurs quickly and involves making inferences, guessing from experience, and basing one perception on another

39 Top-down Processing Evidence
Top-down Processing Evidence Context effects

40 Theories Template Matching Prototype Feature Matching Object-Based
Viewer-Based

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42 What is relationship between activity in the retina & the brain?
An electrode is inserted into various parts of the visual system (retina, cortex) of an animal. The cell’s activity in response to the presentation of visual stimuli (lights, bars, complex images) to the animal’s retina is recorded.

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44 What is a receptive field of retinal ganglion cells?
The receptive field for these cells is the region of the retina that, when stimulated excites or inhibits the cell’s firing pattern.

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46 Are receptive fields of cortical cells like those of retinal ganglion cells?
No!! Our visual cortex cells respond to more complex stimuli (e.g., bars of light).

47 Hubel & Wiesel (1950s & 60s) Recorded cortical cells in the visual cortex of cats in response to visual images they presented to the cat’s retina. They found three types of cells with different receptive fields (bar detectors).

48 Receptive Fields of cortical neurons—Primary Visual cortex
1. Simple Cells --respond to points of light or bars of light in a particular orientation 2. Complex cells --respond to bars of light in a particular orientation moving in a specific direction. 3. Hypercomplex Cells: respond to bars of light in a particular orientation, moving in a specific direction, & of a specific line length.

49 Simple Cells

50 Complex Cells

51 What is the organization of the visual cortex?
Hubel & Wiesel found that the visual cortex is organized into columns. Location specific: For each place on the retina there is a column of cells in cortex. Two columns next to one another in the cortex respond to stimulation of two adjacent points on the retina.

52 Orientation & Ocular Dominance columns in Primary Visual Cortex

53 The Visual cortex has a retinotopic map
Visual cortex has a map of the retina’s surface. More cortical neurons are devoted to fovea of retina. As fovea only has cones, they are widely mapped on cortex’s surface. The reason: cones allow us to see detail & color.

54 Spatial Frequency These grids are low to high spatial frequencies.
Many light bars / square = High S.F. Few light bars / square = Low S.F. Part of vision’s organization

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56 Spatial Frequency By playing with spatial frequency, you can induce a the intense luminance perception of a bright sun.

57 Spatial Frequencies Work Together
Low S.F. give you outlines, High give you details. Broad spectrum give you Local and Global features

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59 Template Theory: Perception as a Cookie Cutter
Basics of template theory Multiple templates are held in memory Compare stimuli to templates in memory for one with greatest overlap until a match is found One click to view the words “See Stimuli” and then the demonstration will illustrate the template theory. All images obtained from Microsoft clips. Search memory for a match See stimuli

60 Template Theory Weakness of theory Problem of imperfect matches
Weakness of theory Problem of imperfect matches Cannot account for the flexibility of pattern recognition system More problems… One click to view the words “See Stimuli”, then the demonstration of the weakness of the theory will occur. All images taken from Microsoft clips. Search for match in memory See stimuli No perfect match in memory

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62 Template Theory More Weaknesses of theory
More Weaknesses of theory Comparison requires identical orientation, size, position of template to stimuli Does not explain how two patterns differ e.g., there’s something wrong with it this, but I can’t put my finger on it – AHA! I see! One click to view the words “See Stimuli”, then the demonstration of the weakness of the theory will occur. All images taken from Microsoft clips.

63 Prototype Theories Modification of template matching (flexible templates) Possesses the average of each individual characteristic No match is perfect; a criterion for matching is needed

64 Prototype Evidence Franks & Bransford (1971)
Prototype Evidence Franks & Bransford (1971) Presented objects based on prototypes Prototype not shown Yet participants are confident they had seen prototype Suggests existence of prototypes

65 Prototype Evidence Solso & McCarthy (1981)
Prototype Evidence Solso & McCarthy (1981) Participants were shown a series of faces Later, a recognition test was given with some old faces, a prototype face, and some new faces that differed in degree from prototype Solso, R.L. & McCarthy, J. E. (1981). Prototype formation of faces: a case of psuedo-memory. British Journal of Psychology, 72,

66 Solso & McCarthy (1981) Results
Solso & McCarthy (1981) Results The red arrow notes that participants were more confident they had seen the prototype than actual items they had seen Solso, R.L. & McCarthy, J. E. (1981). Prototype formation of faces: a case of psuedo-memory. British Journal of Psychology, 72,

67 Research on Prototypes
Research on Prototypes Researchers have found that prototypical faces are found to be more attractive to participants Halberstadt & Rhodes (2000) Examined the impact of prototypes of dogs, wristwatches, and birds on attractiveness of the stimuli Results indicate a strong relationship between averageness and attractiveness of the dogs, birds, and wristwatches

68 Feature Theories Recognize objects on the basis of a small number of characteristics (features) Detect specific elements and assemble them into more complex forms Brain cells that respond to specific features, such as lines and angles are referred to as “feature detectors”

69 Feature Evidence Hubel & Wiesel (1979) using single cell technique
Feature Evidence Hubel & Wiesel (1979) using single cell technique Simple cells detect bars or edges of particular orientation in particular location Complex cells detect bars or edges of particular orientation, exact location abstracted Hypercomplex cells detect particular colors (simple and complex cells), bars, or edges of particular length or moving in a particular direction

70 Selfridge’s (1959) Pandemonium Model of visual word perception where “R” is the target letter.

71 Feature net model by Rumelhart and McClelland (1987), this is an Interactive Activation Model, which means lower and higher layers can both inhibit and excite each other, providing a mechanism for both top-down and bottom-up effects.

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73 Object Recognition Recognition By Components (Biederman; Marr) vs.
View-Based Recognition (Tarr; Bülthoff)

74 Superquadratics (Pentland, 1986)
Geons (Biederman, 1987) Generalized Cylinders (Binford, 1971; Marr, 1982)

75 Recognition By Components (Biederman)
Basic set of geometrical shape Geons (“geometric” + “ions”) Distinguishable from almost any viewing angle Recognizable even with occlusion “Grammatical” relationship b/w parts Part-whole hierarchies

76 Evidence of Geons Beiderman (1987) Can you identify these objects?
Beiderman (1987) Can you identify these objects? Biederman, I.  (1987).  Recognition-by-Components:  A Theory of Human Image Understanding.  Psychological Review, 94, Images from Biederman used with permission. These objects have been rendered unidentifiable because their geons are nonrecoverable

77 Evidence of Geons Beiderman (1987) Can you identify these objects?
Beiderman (1987) Can you identify these objects? Biederman, I.  (1987).  Recognition-by-Components:  A Theory of Human Image Understanding.  Psychological Review, 94, Images from Biederman used with permission. These objects have had the same amount of the object taken out but because the geons can still be recreated, one can recover the objects

78 Testing Biederman Objects are decomposed
Omitting Vertices Retaining Vertices In accordance with theory, easier to identify object with vertices

79 Biederman: Stage 1, extract appropriate geon from image, and stage 2, match to similar representation stored in long-term memory. Biederman proposed that certain properties of 2-D images are non-accidental, representing real properties in the world.

80 Marr’s Computational Approach
Primal Sketch: 2-D description includes changes in light intensity, edges, contours, blobs 2 ½ -D Sketch: Includes information about depth, motion, shading. Representation is observer-centered 3-D Representation: A representation of objects and their relationships, observer-independent.

81 Pros Cons Object Recognition
Explains why it can be hard to recognize familiar objects from highly unusual perspectives Cons Absence of physiological evidence Does not explain expert discriminations or quirks of facial recognition

82 View-Based Recognition
Tarr; Bulthoff Multiple stored views of objects Viewer-centered frame of reference Specific views correspond to specific patterns of neural activation (possibly involves “place neurons”) Match b/w current and stored pattern of activation Interpolating (“educated guessing” or impletion) b/w seen and stored views

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85 Viewer Based Recognition
Physiological evidence Explains behavioral evidence Does not explain how novel objects are learnt

86 The End


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