Eager Eyes: Visuelle Kommunikation in Kunst und Computergrafik

Transcription

1 Eager Eyes: Visuelle Kommunikation in Kunst und Computergrafik Visualisierung, Wahrnehmung, Interaktion

2 Software Visualization Each line of code represented by one line Shows program structure Colored by Age Author Number of errors

3 Text Visualization: SPIRE Shows results of text mining More important topics create higher mountains Similar topics close to each other Development over time with animation

4 Text Visualization: Theme River Importance of topics over time Shows trends, patterns Compact display of the topics of many thousand articles

5 TextArc Show Text along circle Words move towards center Show connections between parts Which word appears where?

6 CodeDOC Use TextArc Idea Program visualizes itself running User input initiates jump

7 SAPPLET Visualize SAP s stock price Spiral for time

8 Visualization and Art Wait times for buses Mondrian style Decorative, but of limited use Skog et al, InfoVis 2003

9 Artifacts of the Presence Era Use noise level to cut layers from pictures Layers behave like sediments (fusion) Visitors can look at past images Viégas et al, InfoVis 2004

10 Layers for FlowVis Translucent layers as used in oil painting Used for different dimensions of flow data Not only vary color but also shape Similar solutions from people with crayons Kirby, Laidlaw, Vis 1999

11 Engaging Visualizations Brush strokes as glyphs Different painterly styles Effective image = Aesthetic image? User study to compare Healey, Enns, CG&A

12 Texture for 3D Shape Perception Different textures show shape more or less effectively Lessons from illustration/ink drawing User studies for comparison Relevant for volume and flow visualization Interrante, Pizer, TVCG 1997

13 Color, Color Scales Colors have different apparent luminance Color scales Isoluminant Increasing/decreasing luminance Similar color steps for all values Calibration for each display

14 The Which Blair Project Use color scale to color grayscale image Recognizable face if luminance increases monotonically Fast, many tests possible Exploit human capability to recognize faces! Rogowitz & Kalvin, Vis 2001

15 Develop color scales Compare color with gray Move slider towards face Same luminance when impossible to distinguish Color scale with different grays Kindlmann et al, Vis 2002

16 Perception Perception is very complex Many interesting phenomena, some useful, some problematic Important to know them to design useful graphical systems and visualizations!

17 Perception vs. Cognition Perception Eye, optical nerve, visual cortex Basic perception First processing (edges, planes) Not conscious Reflexes Cognition Recognizing objects Relations between objects Conclusion drawing Problem solving Learning,

18 Change Blindness in InfoVis Make transitions more obvious Possible to tell change from printed image Tell direction of change from static image Use animation and blending Lowell, Hetzler, Tanasse, InfoVis 2001

19 Gestalt Laws German for shape or form Reasons for objects to be seen as groups Closure Similarity Proximity Symmetry Continuity Common Fate

20 Gestalt Principles Reification: Filling in of missing parts of the image Multistability

21 Emergence Holistic perception of image No part of the image reveals the object See also autostereograms ( The Magic Eye ), etc.

22 Online Resources Pre-attentive Processing, Change Blindness Change Blindness, Inattentional Blindness ColorBrewer

23 Depth of Field (DOF) Known from photography and movies Used for ~150 years Intuitive Human eye has DOF effect, ignores blurred parts

24 Semantic DOF (SDOF) Based on relevance, rather than distance Guides user s attention In-place Focus+Context

25 SDOF Application

26 Preattentive Features Preattentive Features Find targets among distractors Short time (200ms) Detect, locate, estimate percentage Color, orientation, closure, sharpness ;) Tests Detection Location Count Estimate

27 SDOF Study Results All results are significantly better than chance Accuracy for location very good (>90%) or good (>60%), depending on blur level Differentiation between sharp and slightly blurred objects difficult Accuracy almost identical for cases with and without targets (except for lowest blur) Accuracy for count estimation good (>85% for the two higher blur levels, 74% for lowest blur level) Proper parameterization for viewing conditions is necessary Subjects see difference but cannot quantify it (similar to color!) Participants did not like looking at blurred objects

28 SDOF Study Conclusions Many small results (numbers) Interesting insights Remarks from test subjects Found problems in study setup Program bugs Insufficient number of tries Complexity of applications

29 Treemaps for Interaction Quantum Treemaps: PhotoMesa Quick and simple navigation of large photo library Hierarchical structure immediately visible

30 Bubble Treemaps Extension of Treemaps Can use any shape, not just rectangles More organic Better use of space by filling gaps

31 Music Library Browser Treemap display of music collection Genre, Artist, Album, etc. Albums represented by cover Large data size (1000s of albums) Tom Butkiewicz

32 Focus+Context (F+C) Abstract data space Environment of data important Give more room/attention to focus, but keep context F+C Techniques Geometrical/distortion oriented Magic Lenses In-Place Require Interaction

33 Distortion-oriented F+C Fisheye Views Similar to fisheye lens! More abstract use in TableLens Show numbers for focus values Show bars/glyphs for context

34 Magic Lenses Window that shows Additional and/or Different information In 2D or 3D Avoid cluttering display Present detail on demand See information visualization mantra

35 In-place F+C Semantic Depth of Field (SDOF) Generalize Depth of Field Very effective (user study)

36 Interaction Interaction makes visualization useful Query of data Information drill-down Navigation in data Information Visualization Mantra (Shneiderman, 1996) Overview first, zoom and filter, then detail on demand