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. 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.

4. 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)

5. 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

7. Common Fate

8. 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

9. Gestalt Laws
Laws of Grouping
Closure/ convexity

10. 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

11. 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?

12. · 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:

13. Brains see two instead of all of these interpretations? Why not?
Figure 1.5. “Subjective” perceptions are not necessarily “arbitrary” perceptions
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.
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.

14. Bi-stable Images

15. Bi-stable Images

20. Law of One in Audition Shepard Tone
Each square in the figure indicates a tone, any set of squares in vertical alignment together making one Shepard tone. The color of each square indicates the loudness of the note, with purple being the quietest and green the loudest. Overlapping notes that play at the same time are exactly one octave apart, and each scale fades in and fades out so that hearing the beginning or end of any given scale is impossible.

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

22. Object Recognition Mike the blind guy given sight

23. 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?

24. What letter are these, and how do you know?

25. Object Recognition

27. 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.

28. 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.

29. 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

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

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

34. Bottom-Up Processing
Perception comes from the stimuli in the environment
Parts are identified, put together, and then recognition occurs
Context does not matter

35. Gibson’s Direct Perception (Bottom-Up)
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

36. Top-down Processing Perception is not automatic from raw stimuli
Top-down Processing
Perception is not automatic from raw stimuli
Context is needed to build perception
Meaning is constructed by making inferences, guessing from experience, and basing one perception on another

37. 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

38. 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

39. 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.

40. 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”

41. Two Feature Theories of Object Recognition
Recognition By Components (Biederman; Marr)
vs.
View-Based Recognition (Tarr; Bülthoff)

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

43. 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

44. 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

45. 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

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

47. 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

48. 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.

49. 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

53. The End

54. Opponent Process in a Movement Illusion: Waterfall Effect

55. 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.

56. 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

58. X

59. X

60. X

61. X X X

62. X X X

63. Top-Down & Bottom-Up

65. Orientation & Ocular Dominance columns in Primary Visual Cortex

66. Simple Cells

67. Complex Cells

68. 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.

69. 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.

70. Spatial Frequency in Action

71. Top-down Processing Evidence
Top-down Processing Evidence
Context effects

72. Theories Template Matching Prototype Feature Matching Object-Based
Viewer-Based

73. Change Blindness
Counter experiment:
Campus Door Demo:
Construction door
Gradual Change:

75. 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

76. 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

77. 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,

78. 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,

79. 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

80. 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

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

82. 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.

84. 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.

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