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Cecilia R. Aragon IEOR 170 UC Berkeley Spring 2006

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1 Cecilia R. Aragon IEOR 170 UC Berkeley Spring 2006
Visual Perception Cecilia R. Aragon IEOR 170 UC Berkeley Spring 2006

2 Acknowledgments Thanks to slides and publications by Pat Hanrahan, Christopher Healey, Maneesh Agrawala, and Lawrence Anderson-Huang. Spring 2006 IEOR 170

3 Visual perception Structure of the Retina Preattentive Processing
Detection Estimating Magnitude Change Blindness Multiple Attributes Gestalt Spring 2006 IEOR 170

4 Visual perception and psychophysics
Psychophysics is concerned with establishing quantitative relations between physical stimulation and perceptual events. Spring 2006 IEOR 170

5 Structure of the Retina
Spring 2006 IEOR 170

6 Structure of the Retina
The retina is not a camera! Network of photo-receptor cells (rods and cones) and their connections [Anderson-Huang, L. Spring 2006 IEOR 170

7 Photo-transduction When a photon enters a receptor cell (e.g. a rod or cone), it is absorbed by a molecule called 11-cis-retinal and converted to trans form. The different shape causes it to ultimately reduce the electrical conductivity of the photo-receptor cell. [Anderson-Huang, L. Spring 2006 IEOR 170

8 Electric currents from photo-receptors
Photo-receptors generate an electrical current in the dark. Light shuts off the current. Each doubling of light causes roughly the same reduction of current (3 picoAmps for cones, 6 for rods). Rods more sensitive, recover more slowly. Cones recover faster, overshoot. Geometrical response in scaling laws of perception. [Anderson-Huang, L. .utoledo.edu/~lsa/_color/18_retina.htm] Spring 2006 IEOR 170

9 Preattentive Processing

10 How many 5’s? [Slide adapted from Joanna McGrenere ] Spring 2006 IEOR 170

11 How many 5’s? Spring 2006 IEOR 170

12 Preattentive Processing
Certain basic visual properties are detected immediately by low-level visual system “Pop-out” vs. serial search Tasks that can be performed in less than 200 to 250 milliseconds on a complex display Eye movements take at least 200 msec to initiate Spring 2006 IEOR 170

13 Color (hue) is preattentive
Detection of red circle in group of blue circles is preattentive [image from Healey 2005] Spring 2006 IEOR 170

14 Form (curvature) is preattentive
Curved form “pops out” of display [image from Healey 2005] Spring 2006 IEOR 170

15 Conjunction of attributes
Conjunction target generally cannot be detected preattentively (red circle in sea of red square and blue circle distractors) [image from Healey 2005] Spring 2006 IEOR 170

16 Healey applet on preattentive processing
Spring 2006 IEOR 170

17 Preattentive Visual Features
closure color (hue) intensity flicker direction of motion stereoscopic depth 3D depth cues line orientation length width size curvature number terminators intersection Spring 2006 IEOR 170

18 line (blob) orientation
Spring 2006 IEOR 170

19 length, width Spring 2006 IEOR 170

20 closure Spring 2006 IEOR 170

21 size Spring 2006 IEOR 170

22 curvature Spring 2006 IEOR 170

23 density, contrast Spring 2006 IEOR 170

24 intersection Spring 2006 IEOR 170

25 terminators Spring 2006 IEOR 170

26 flicker Spring 2006 IEOR 170

27 direction of motion Spring 2006 IEOR 170

28 velocity of motion Spring 2006 IEOR 170

29 Cockpit dials Detection of a slanted line in a sea of vertical lines is preattentive Spring 2006 IEOR 170

30 Detection Spring 2006 IEOR 170

31 Just-Noticeable Difference
Which is brighter? Spring 2006 IEOR 170

32 Just-Noticeable Difference
Which is brighter? (130, 130, 130) (140, 140, 140) Spring 2006 IEOR 170

33 Weber’s Law In the 1830’s, Weber made measurements of the just-noticeable differences (JNDs) in the perception of weight and other sensations. He found that for a range of stimuli, the ratio of the JND ΔS to the initial stimulus S was relatively constant: ΔS / S = k Spring 2006 IEOR 170

34 Weber’s Law Ratios more important than magnitude in stimulus detection
For example: we detect the presence of a change from 100 cm to 101 cm with the same probability as we detect the presence of a change from 1 to 1.01 cm, even though the discrepancy is 1 cm in the first case and only .01 cm in the second. Spring 2006 IEOR 170

35 Weber’s Law Most continuous variations in magnitude are perceived as discrete steps Examples: contour maps, font sizes Spring 2006 IEOR 170

36 Estimating Magnitude Spring 2006 IEOR 170

37 Stevens’ Power Law Compare area of circles: Spring 2006 IEOR 170

38 [graph from Wilkinson 99]
Stevens’ Power Law s(x) = axb s is the sensation x is the intensity of the attribute a is a multiplicative constant b is the power b > 1: overestimate b < 1: underestimate [graph from Wilkinson 99] Spring 2006 IEOR 170

39 Stevens’ Power Law [Stevens 1961] Spring 2006 IEOR 170

40 Stevens’ Power Law Experimental results for b: Length .9 to 1.1
Area .6 to .9 Volume .5 to .8 Heuristic: b ~ 1/sqrt(dimensionality) Spring 2006 IEOR 170

41 [Cartography: Thematic Map Design, p. 170, Dent, 96]
Stevens’ Power Law Apparent magnitude scaling [Cartography: Thematic Map Design, p. 170, Dent, 96] S = 0.98A0.87 [J. J. Flannery, The relative effectiveness of some graduated point symbols in the presentation of quantitative data, Canadian Geographer, 8(2), pp , 1971] [slide from Pat Hanrahan] Spring 2006 IEOR 170

42 Relative Magnitude Estimation
Most accurate Least accurate Position (common) scale Position (non-aligned) scale Length Slope Angle Area Volume Color (hue/saturation/value) Spring 2006 IEOR 170

43 Change Blindness Spring 2006 IEOR 170

44 Change Blindness An interruption in what is being seen causes us to miss significant changes that occur in the scene during the interruption. Demo from Ron Rensink: Spring 2006 IEOR 170

45 Possible Causes of Change Blindness
[Simons, D. J. (2000), Current approaches to change blindness, Visual Cognition, 7, ] Spring 2006 IEOR 170

46 Multiple Visual Attributes
Spring 2006 IEOR 170

47 The Game of Set Color Symbol Number Shading
A set is 3 cards such that each feature is EITHER the same on each card OR is different on each card. [Set applet by Adrien Treuille, washington.edu/homes/treuille/resc/set/] Spring 2006 IEOR 170

48 Multiple Visual Attributes
Integral vs. separable Integral dimensions two or more attributes of an object are perceived holistically (e.g.width and height of rectangle). Separable dimensions judged separately, or through analytic processing (e.g. diameter and color of ball). Separable dimensions are orthogonal. For example, position is highly separable from color. In contrast, red and green hue perceptions tend to interfere with each other. Spring 2006 IEOR 170

49 Integral vs. Separable Dimensions
[Ware 2000] Spring 2006 IEOR 170

50 Gestalt Spring 2006 IEOR 170

51 Spring 2006 IEOR 170

52 Gestalt This law says that we try to experience things in as good a gestalt way as possible. In this sense, "good" can mean several things, such as regular, orderly, simplistic, symmetrical, etc. The other gestalt laws are: Spring 2006 IEOR 170

53 Gestalt Principles figure/ground proximity similarity symmetry
connectedness continuity closure common fate transparency Spring 2006 IEOR 170

54 Figure-ground Figure-ground minds have an innate tendency to perceive one aspect of an event as the figure or foreground and the other as the ground or the background. Spring 2006 IEOR 170

55 proximity Spring 2006 IEOR 170

56 similarity Spring 2006 IEOR 170

57 symmetry Spring 2006 IEOR 170

58 connectedness Spring 2006 IEOR 170

59 continuity Spring 2006 IEOR 170

60 closure Spring 2006 IEOR 170

61 Classical Principles of Grouping (I)
Spring 2006 IEOR 170

62 Classical Principles of Grouping (II)
Spring 2006 IEOR 170

63 Connectedness [from Ware 2004]
Examples Proximity Connectedness [from Ware 2004] Figure/Ground [ Spring 2006 IEOR 170

64 Visual Completion Spring 2006 IEOR 170

65 Edge Relatability Spring 2006 IEOR 170

66 Illusory Contours 5.3.2 Spring 2006 IEOR 170

67 Illusory Contours (II)
Spring 2006 IEOR 170

68 Depth perception Oculomotor Visual Acoomodation Binocular Covegence
muscle feedback control signal Visual Binocular Monocular Static cues Interposition Size Perspective Motion parallax Spring 2006 IEOR 170

69 Depth perception Perspective Linear perspective Texture gradient
Aerial-perspective Shadow Spring 2006 IEOR 170

70 Size Spring 2006 IEOR 170

71 Spring 2006 IEOR 170

72 Spring 2006 IEOR 170

73 Spring 2006 IEOR 170

74 Linear perspective Spring 2006 IEOR 170

75 Aerial Perspective Spring 2006 IEOR 170

76 Texture gradient Spring 2006 IEOR 170

77 Shades and Shadows Spring 2006 IEOR 170

78 Shades and Shadows Spring 2006 IEOR 170

79 Overlapping Spring 2006 IEOR 170

80 Motion Spring 2006 IEOR 170

81 motion parallax Spring 2006 IEOR 170

82 Spring 2006 IEOR 170

83 Conclusion What is currently known about visual perception can aid the design process. Understanding low-level mechanisms of the visual processing system and using that knowledge can result in improved displays. Spring 2006 IEOR 170

84 Spring 2006 IEOR 170

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