Visual Perception Cecilia R Aragon IEOR 170 UC
- Slides: 84
Visual Perception Cecilia R. Aragon IEOR 170 UC Berkeley Spring 2006 IEOR 170
Acknowledgments • Thanks to slides and publications by Pat Hanrahan, Christopher Healey, Maneesh Agrawala, and Lawrence Anderson-Huang. Spring 2006 IEOR 170 2
Visual perception • • Structure of the Retina Preattentive Processing Detection Estimating Magnitude Change Blindness Multiple Attributes Gestalt Spring 2006 IEOR 170 3
Visual perception and psychophysics Psychophysics is concerned with establishing quantitative relations between physical stimulation and perceptual events. Spring 2006 IEOR 170 4
Structure of the Retina Spring 2006 IEOR 170 5
Structure of the Retina • The retina is not a camera! • Network of photo-receptor cells (rods and cones) and their connections [Anderson-Huang, L. http: //www. physics. utoledo. edu/~lsa/ _color/18_retina. htm] Spring 2006 IEOR 170 6
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. http: //www. physics. utoledo. edu/~lsa/_color/18_retina. htm] Spring 2006 IEOR 170 7
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 pico. Amps for cones, 6 for rods). • Rods more sensitive, recover more slowly. • Cones recover faster, overshoot. • Geometrical response in scaling laws of perception. Spring 2006 [Anderson-Huang, L. http: //www. physics. utoledo. edu/~lsa/_color/18_retina. htm] IEOR 170 8
Preattentive Processing Spring 2006 IEOR 170
How many 5’s? 385720939823728196837293827 382912358383492730122894839 909020102032893759273091428 938309762965817431869241024 [Slide adapted from Joanna Mc. Grenere http: //www. cs. ubc. ca/~joanna/ ] Spring 2006 IEOR 170 10
How many 5’s? 385720939823728196837293827 382912358383492730122894839 909020102032893759273091428 938309762965817431869241024 Spring 2006 IEOR 170 11
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 12
Color (hue) is preattentive • Detection of red circle in group of blue circles is preattentive [image from Healey 2005] Spring 2006 IEOR 170 13
Form (curvature) is preattentive • Curved form “pops out” of display [image from Healey 2005] Spring 2006 IEOR 170 14
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 15
Healey applet on preattentive processing http: //www. csc. ncsu. edu/faculty/healey/PP/index. html Spring 2006 IEOR 170 16
Preattentive Visual Features line orientation length width size curvature number terminators intersection Spring 2006 closure color (hue) intensity flicker direction of motion stereoscopic depth 3 D depth cues IEOR 170 17
line (blob) orientation Spring 2006 IEOR 170 18
length, width Spring 2006 IEOR 170 19
closure Spring 2006 IEOR 170 20
size Spring 2006 IEOR 170 21
curvature Spring 2006 IEOR 170 22
density, contrast Spring 2006 IEOR 170 23
intersection Spring 2006 IEOR 170 24
terminators Spring 2006 IEOR 170 25
flicker Spring 2006 IEOR 170 26
direction of motion Spring 2006 IEOR 170 27
velocity of motion Spring 2006 IEOR 170 28
Cockpit dials • Detection of a slanted line in a sea of vertical lines is preattentive Spring 2006 IEOR 170 29
Detection Spring 2006 IEOR 170 30
Just-Noticeable Difference • Which is brighter? Spring 2006 IEOR 170 31
Just-Noticeable Difference • Which is brighter? (130, 130) Spring 2006 (140, 140) IEOR 170 32
Weber’s Law • In the 1830’s, Weber made measurements of the justnoticeable 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 33
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 34
Weber’s Law • Most continuous variations in magnitude are perceived as discrete steps • Examples: contour maps, font sizes Spring 2006 IEOR 170 35
Estimating Magnitude Spring 2006 IEOR 170 36
Stevens’ Power Law • Compare area of circles: Spring 2006 IEOR 170 37
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 Spring 2006 [graph from Wilkinson 99] IEOR 170 38
Stevens’ Power Law [Stevens 1961] Spring 2006 IEOR 170 39
Stevens’ Power Law Experimental results for b: Length Area Volume . 9 to 1. 1. 6 to. 9. 5 to. 8 Heuristic: b ~ 1/sqrt(dimensionality) Spring 2006 IEOR 170 40
Stevens’ Power Law • Apparent magnitude scaling [Cartography: Thematic Map Design, p. 170, Dent, 96] S = 0. 98 A 0. 87 [J. J. Flannery, The relative effectiveness of some graduated point symbols in the presentation of quantitative data, Canadian Geographer, 8(2), pp. 96 -109, 1971] [slide from Pat Hanrahan] Spring 2006 IEOR 170 41
Relative Magnitude Estimation Most accurate Position (common) scale Position (non-aligned) scale Length Slope Angle Least accurate Spring 2006 Area Volume Color (hue/saturation/value) IEOR 170 42
Change Blindness Spring 2006 IEOR 170 43
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: http: //www. psych. ubc. ca/~rensink/flicker/ Spring 2006 IEOR 170 44
Possible Causes of Change Blindness [Simons, D. J. (2000), Current approaches to change blindness, Visual Cognition, 7, 1 -16. ] Spring 2006 IEOR 170 45
Multiple Visual Attributes Spring 2006 IEOR 170 46
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, http: //www. cs. washington. edu/homes/treuille/resc/set/] Spring 2006 IEOR 170 47
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 48
Integral vs. Separable Dimensions Integral Separable [Ware 2000] Spring 2006 IEOR 170 49
Gestalt Spring 2006 IEOR 170 50
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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 52
Gestalt Principles • • • figure/ground proximity similarity symmetry connectedness continuity closure common fate transparency Spring 2006 IEOR 170 53
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 54
proximity Spring 2006 IEOR 170 55
similarity Spring 2006 IEOR 170 56
symmetry Spring 2006 IEOR 170 57
connectedness Spring 2006 IEOR 170 58
continuity Spring 2006 IEOR 170 59
closure Spring 2006 IEOR 170 60
Classical Principles of Grouping (I) Spring 2006 IEOR 170 61
Classical Principles of Grouping (II) Spring 2006 IEOR 170 62
Examples Proximity Connectedness [from Ware 2004] Figure/Ground [http: //www. aber. ac. uk/media/Modules/MC 10220/visper 07. html] Spring 2006 IEOR 170 63
Visual Completion Spring 2006 IEOR 170 64
Edge Relatability Spring 2006 IEOR 170 65
Illusory Contours 5. 3. 2 Spring 2006 IEOR 170 66
Illusory Contours (II) Spring 2006 IEOR 170 67
Depth perception • Oculomotor • Visual – Acoomodation – Covegence • muscle feedback • control signal – Binocular – Monocular • Static cues – Interposition – Size – Perspective • Motion parallax Spring 2006 IEOR 170 68
Depth perception – Perspective • Linear perspective • Texture gradient • Aerial-perspective • Shadow Spring 2006 IEOR 170 69
Size Spring 2006 IEOR 170 70
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Linear perspective Spring 2006 IEOR 170 74
Aerial Perspective Spring 2006 IEOR 170 75
Texture gradient Spring 2006 IEOR 170 76
Shades and Shadows Spring 2006 IEOR 170 77
Shades and Shadows Spring 2006 IEOR 170 78
Overlapping Spring 2006 IEOR 170 79
Motion Spring 2006 IEOR 170 80
motion parallax Spring 2006 IEOR 170 81
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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 83
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