Why Should We Be Interested In Visualization. Intro to Human Visual System and Displays. Basic Pathways. Perceptual versus Cultural A B C D

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1 Intro to Human Visual System and Displays Fundamental Optics Fovea Perception These slides were developed by Colin Ware, Univ. of New Hampshire Why Should We Be Interested In Visualization Hi bandwidth to the brain (70% of all receptors,40+% of cortex, 4 billion neurons) Can see much more than we can mentally image Can perceive patterns (what dimensionality?) Perceptual versus Cultural Basic Pathways DORSAL PATHWAYS Eye Movement Control PP VENTRAL PATHWAYS STS IT Faces, Attention, Short term Memory A B DP VIP LIP 7A MST FST TEO C D Dynamic form PO VISUALLY GUIDED MOTION PERCEPTION TRANSIENT V3A MT V3 V2 V1 V4 Filtering for orientation, color, stereo depth Color and form with color, attention OBJECT PERCEPTION COLOR CONSTANCY ATTENTION FACES MEMORY SUSTAINED

2 The machinery Human Visual Field A B Parallel processing D of orientation, texture, color and motion features Detection of 2D patterns, contours and regions C Object Identification, Working Memory LEFT RIGHT Visual Angle Acuities r θ d h Vernier super acuity (10 sec) Grating acuity Two Point acuity (0.5 min)

3 Human Spatial Acuity Cutoff at 50 cycles/deg. Receptors: 20 sec of arc Pooled over larger and larger areas 100 million receptors 1 million fibers to brain A screen may have 30 pixels/cm need about 4 times as much. VR displays have 5 pixels/cm Acuity Distribution Brain Pixels Distance from Fovea (deg.)

4 Brain pixels=retinal ganglion cell receptive fields Pixels and Brain Pixels 0.8 BP Field size = 0.006(e+1.0) - Anderson Characters = 0.046e - Anstis Ganglion cells bp Distance from Fovea (deg.) Distance from Fovea (deg.) Small Screen 0.2 BP Big Screen Tartufieri Perception Many, many ways to trick the vision system.

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6 Intro to Color for Information Display Color Theory Color Geometries Color applications Labeling Pseudo-color sequences Trichromacy Cone sensitivity functions Three cones types in retina a G+B +R b Wavelength (nm)

7 Color measurement Short wavelength sensitive cones Based on the standard observer CIE tristimulus values XYX Y is luminance. Assumes all humans are the same Blue text on a dark background is to be avoided. We have very few short-wavelength sensitive cones in the retina and they are not very sensitive Blue text on dark background is to be avoided. We have very few short-wavelength sensitive cones in the retina and they are not very sensitive Blue text on a dark background is to be avoided. We have very few short-wavelength sensitive cones in the retina and they are not very sensitive. Chromatic aberration in the eye is also a problem Blue text on a dark background is to be avoided. We have very few short-wavelength sensitive cones in the retina and they are not very sensitive Color Channels Long (red) Med (green) Short (blue) Luminance R-G Y-B Luminance channel Visual system extracts surface information Discounts illumination level Discounts color of illumination Mechanisms 1) Adaptation 2) Simultaneous contrast

8 Luminance is not Brightness Luminance contrast Eye sensitive over 9 orders or magnitude 5 orders of magnitude (room sunlight) Receptors bleach and become less sensitive with more light Takes up to half an hour to recover sensitivity We are not light meters Contrast for constancy Contrast for constancy

9 Brightness Lightness and Luminance Luminance for Shape-fromshading Brightness refers to perception of lights Brightness non linear Monitor Gamma Lightness refers to perception of surfaces Perceived lightness depends on a reference white Channel Properties Chromatic Channels have Low Spatial Resolution Luminance Channel Detail Form Shading Motion Stereo Chromatic Channels Surfaces of things Labels Berlin and Kay Categories (about 6-10) Red, green, yellow and blue are special (unique hues) Luminance contrast needed to see detail 3:1 recommended 10:1 idea for small text Some Natural philosophers suppose that these colors arise from accidental vapours diffused in the air, which communicate their own hues to the shadows; so that the colours of the shadows are occasioned by the reflection of any given sky colour: the above observations favour this opinion. Some Natural philosophers suppose that these colors arise from accidental vapours diffused in the air, which communicate their own hues to the shadows; Text on an isoluminant background is hard to read

10 Color phenomena Color blindness Chromatic contrast Small field tritanopia b a A 3D to a 2D space 8 % of males R-G color blindness d c Can generate color blind acceptable palette Yellow blue variation OK Implications Color perception is relative We are sensitive to small differenceshence need sixteen million colors Not sensitive to absolute values- hence we can only use < 10 colors for coding Color great for classification Rapid visual segmentation Color helps us determine type Only about six categories white black red green yellow yellow green blue brown pink purple orange grey

11 Applications Color interfaces Color coding Color sequences Color for multi-dimensional discrete data Color Coding Large areas: low saturation Small areas high saturation Break isoluminance with borders Color Coding Visual Principles The same rules apply to color coding text and other similar information. Small areas should have high saturation colors, Large areas should be coded with low saturation colors Sensory vs. Arbitrary Symbols Pre-attentive Properties Gestalt Properties Relative Expressiveness of Visual Cues Luminance contrast should be maintained

12 Sensory vs. Arbitrary Symbols Sensory: Understanding without training Resistance to instructional bias Sensory immediacy Hard-wired and fast Cross-cultural Validity Arbitrary Hard to learn Easy to forget Embedded in culture and applications American Sign Language Primarily arbitrary, but partly representational Signs sometimes based partly on similarity But you couldn t guess most of them They differ radically across languages Sublanguages in ASL are more representative Diectic terms Describing the layout of a room, there is a way to indicate by pointing on a plane where different items sit. Pre-attentive Processing A limited set of visual properties are processed pre-attentively (without need for focusing attention). This is important for design of visualizations What can be perceived immediately? What properties are good discriminators? What can mislead viewers? Example: Color Selection Viewer can rapidly and accurately determine whether the target (red circle) is present or absent. Difference detected in color. All Preattentive Processing figures from Healey 97

13 Example: Shape Selection Pre-attentive Processing Viewer can rapidly and accurately determine whether the target (red circle) is present or absent. Difference detected in form (curvature) < ms qualifies as pre-attentive eye movements take at least 200ms yet certain processing can be done very quickly, implying low-level processing in parallel If a decision takes a fixed amount of time regardless of the number of distracters, it is considered to be pre-attentive. Example: Conjunction of Features Example: Emergent Features Viewer cannot rapidly and accurately determine whether the target (red circle) is present or absent when target has two or more features, each of which are present in the distractors. Viewer must search sequentially. All Preattentive Processing figures from Healey 97 Target has a unique feature with respect to distractors (open sides) and so the group can be detected preattentively.

14 Example: Emergent Features Asymmetric and Graded Preattentive Properties Some properties are asymmetric a sloped line among vertical lines is preattentive a vertical line among sloped ones is not Some properties have a gradation some more easily discriminated among than others Target does not have a unique feature with respect to distractors and so the group cannot be detected preattentively. Use Grouping of Well-Chosen Shapes for Displaying Multivariate Data SUBJECT PUNCHED QUICKLY OXIDIZED TCEJBUS DEHCNUP YLKCIUQ DEZIDIXO CERTAIN QUICKLY PUNCHED METHODS NIATREC YLKCIUQ DEHCNUP SDOHTEM SCIENCE ENGLISH RECORDS COLUMNS ECNEICS HSILGNE SDROCER SNMULOC GOVERNS PRECISE EXAMPLE MERCURY SNREVOG ESICERP ELPMAXE YRUCREM CERTAIN QUICKLY PUNCHED METHODS NIATREC YLKCIUQ DEHCNUP SDOHTEM GOVERNS PRECISE EXAMPLE MERCURY SNREVOG ESICERP ELPMAXE YRUCREM SCIENCE ENGLISH RECORDS COLUMNS ECNEICS HSILGNE SDROCER SNMULOC SUBJECT PUNCHED QUICKLY OXIDIZED TCEJBUS DEHCNUP YLKCIUQ DEZIDIXO CERTAIN QUICKLY PUNCHED METHODS NIATREC YLKCIUQ DEHCNUP SDOHTEM SCIENCE ENGLISH RECORDS COLUMNS ECNEICS HSILGNE SDROCER SNMULOC

15 Text NOT Preattentive SUBJECT PUNCHED QUICKLY OXIDIZED TCEJBUS DEHCNUP YLKCIUQ DEZIDIXO CERTAIN QUICKLY PUNCHED METHODS NIATREC YLKCIUQ DEHCNUP SDOHTEM SCIENCE ENGLISH RECORDS COLUMNS ECNEICS HSILGNE SDROCER SNMULOC GOVERNS PRECISE EXAMPLE MERCURY SNREVOG ESICERP ELPMAXE YRUCREM CERTAIN QUICKLY PUNCHED METHODS NIATREC YLKCIUQ DEHCNUP SDOHTEM GOVERNS PRECISE EXAMPLE MERCURY SNREVOG ESICERP ELPMAXE YRUCREM SCIENCE ENGLISH RECORDS COLUMNS ECNEICS HSILGNE SDROCER SNMULOC SUBJECT PUNCHED QUICKLY OXIDIZED TCEJBUS DEHCNUP YLKCIUQ DEZIDIXO CERTAIN QUICKLY PUNCHED METHODS NIATREC YLKCIUQ DEHCNUP SDOHTEM SCIENCE ENGLISH RECORDS COLUMNS ECNEICS HSILGNE SDROCER SNMULOC Preattentive Visual Properties (Healey 97) length Triesman & Gormican [1988] width Julesz [1985] size Triesman & Gelade [1980] curvature Triesman & Gormican [1988] number Julesz [1985]; Trick & Pylyshyn [1994] terminators Julesz & Bergen [1983] intersection Julesz & Bergen [1983] closure Enns [1986]; Triesman & Souther [1985] colour (hue) Nagy & Sanchez [1990, 1992]; D'Zmura [1991] Kawai et al. [1995]; Bauer et al. [1996] intensity Beck et al. [1983]; Triesman & Gormican [1988] flicker Julesz [1971] direction of motion Nakayama & Silverman [1986]; Driver & McLeod [1992] binocular lustre Wolfe & Franzel [1988] stereoscopic depth Nakayama & Silverman [1986] 3-D depth cues Enns [1990] lighting direction Enns [1990] Gestalt Principles Idea: forms or patterns transcend the stimuli used to create them. Why do patterns emerge? Under what circumstances? Gestalt Properties Proximity Principles of Pattern Recognition gestalt German for pattern or form, configuration Original proposed mechanisms turned out to be wrong Rules themselves are still useful Why perceive pairs vs. triplets? 59 Slide adapted from Tamara Munzner

16 Gestalt Properties Similarity Gestalt Properties Continuity 61 Slide adapted from Tamara Munzner Slide adapted from Tamara Munzner 62 Slide adapted from Tamara Munzner Slide adapted from Tamara Munzner Gestalt Properties Connectedness Gestalt Properties Closure 63 Slide adapted from Tamara Munzner Slide adapted from Tamara Munzner 64 Slide adapted from Tamara Munzner Slide adapted from Tamara Munzner

17 Gestalt Properties Symmetry Gestalt Laws of Perceptual Organization (Kaufman 74) Figure and Ground Escher illustrations are good examples Vase/Face contrast Subjective Contour 65 Slide adapted from Tamara Munzner Slide adapted from Tamara Munzner More Gestalt Laws Law of Common Fate like preattentive motion property move a subset of objects among similar ones and they will be perceived as a group Pseudo-color sequences Issues: How can we see forms (quality) How we read value (quantity)

18 Pseudo-Color Sequences Gray scale Spectrum sequence Color Sequences for Maps Color is poor for form and shape Color is naturally classified Luminance is good for form and shape Luminance results in contrast illusions A spiral sequence in color space - a good solution

19 Spiral Sequence Luminance to signal direction Take home messages Use luminance for detail, shape and form Use color for coding - few colors Minimize contrast effects Strong colors for small areas - contrast in luminance with background Subtle colors can be used to segment large areas