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

2. IEOR 1702 Acknowledgments Thanks to slides and publications by Pat Hanrahan, Christopher Healey, Maneesh Agrawala, and Lawrence Anderson-Huang.

3. Spring 2006IEOR 1703 Visual perception Structure of the Retina Preattentive Processing Detection Estimating Magnitude Change Blindness Multiple Attributes Gestalt

4. Spring 2006IEOR 1704 Visual perception and psychophysics Psychophysics is concerned with establishing quantitative relations between physical stimulation and perceptual events.

5. Spring 2006IEOR 1705 Structure of the Retina

6. Spring 2006IEOR 1706 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]

7. Spring 2006IEOR 1707 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]

8. Spring 2006IEOR 1708 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. http://www.physics.utoledo.edu/~lsa/_color/18_retina.htm]

9. Preattentive Processing

10. Spring 2006IEOR 17010 How many 5’s? 385720939823728196837293827 382912358383492730122894839 909020102032893759273091428 938309762965817431869241024 [Slide adapted from Joanna McGrenere http://www.cs.ubc.ca/~joanna/ ]

11. Spring 2006IEOR 17011 How many 5’s? 385720939823728196837293827 382912358383492730122894839 909020102032893759273091428 938309762965817431869241024

12. Spring 2006IEOR 17012 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

13. Spring 2006IEOR 17013 Color (hue) is preattentive Detection of red circle in group of blue circles is preattentive [image from Healey 2005]

14. Spring 2006IEOR 17014 Form (curvature) is preattentive Curved form “pops out” of display [image from Healey 2005]

15. Spring 2006IEOR 17015 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]

16. Spring 2006IEOR 17016 Healey applet on preattentive processing http://www.csc.ncsu.edu/faculty/healey/PP/index.html

17. Spring 2006IEOR 17017 Preattentive Visual Features line orientation length width size curvature number terminators intersection closure color (hue) intensity flicker direction of motion stereoscopic depth 3D depth cues

18. Spring 2006IEOR 17018 Cockpit dials Detection of a slanted line in a sea of vertical lines is preattentive

19. Spring 2006IEOR 17019 Detection

20. Spring 2006IEOR 17020 Just-Noticeable Difference Which is brighter?

21. Spring 2006IEOR 17021 Just-Noticeable Difference Which is brighter? (130, 130, 130)(140, 140, 140)

22. Spring 2006IEOR 17022 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

23. Spring 2006IEOR 17023 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.

24. Spring 2006IEOR 17024 Weber’s Law Most continuous variations in magnitude are perceived as discrete steps Examples: contour maps, font sizes

25. Spring 2006IEOR 17025 Estimating Magnitude

26. Spring 2006IEOR 17026 Stevens’ Power Law Compare area of circles:

27. Spring 2006IEOR 17027 Stevens’ Power Law s(x) = ax b 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]

28. Spring 2006IEOR 17028 Stevens’ Power Law [Stevens 1961]

29. Spring 2006IEOR 17029 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)

30. Spring 2006IEOR 17030 Stevens’ Power Law Apparent magnitude scaling [Cartography: Thematic Map Design, p. 170, Dent, 96] S = 0.98A 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]

31. Spring 2006IEOR 17031 Relative Magnitude Estimation Most accurate Least accurate Position (common) scale Position (non-aligned) scale Length Slope Angle Area Volume Color (hue/saturation/value)

32. Spring 2006IEOR 17032 Change Blindness

33. Spring 2006IEOR 17033 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/

34. Spring 2006IEOR 17034 Possible Causes of Change Blindness [Simons, D. J. (2000), Current approaches to change blindness, Visual Cognition, 7, 1-16. ]

35. Spring 2006IEOR 17035 Multiple Visual Attributes

36. Spring 2006IEOR 17036 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/]

37. Spring 2006IEOR 17037 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.

38. Spring 2006IEOR 17038 Integral vs. Separable Dimensions Integral Separable [Ware 2000]

39. Spring 2006IEOR 17039 Gestalt

40. Spring 2006IEOR 17040 Gestalt Principles figure/ground proximity similarity symmetry connectedness continuity closure common fate transparency

41. Spring 2006IEOR 17041 Examples Figure/Ground [http://www.aber.ac.uk/media/Modules/MC10220/visper07.html] Proximity Connectedness [from Ware 2004]

42. Spring 2006IEOR 17042 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.