Melange: Space Folding for Multi-Focus Interaction
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Transcript of Melange: Space Folding for Multi-Focus Interaction
MélangeSpace Folding for Multi-Focus
Interaction
Niklas ElmqvistNathalie HenryYann Riche
Jean-Daniel Fekete
CHI 2008 – Florence, Italy
Motivation
• Large visual spaces in information visualization– Social networks
• Several focus points– High precision– High detail– Overview?
• Multi-focus interaction
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Multi-Focus Interaction
Example: Planning a trip to Florence
distance?
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Solution: Split-Screen
• Show the foci as two different views
?
Mélange
Demonstration!
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Generalizing RequirementsG1: Guaranteed focus visibility
• Montreal and Florence
G2: Surrounding context visibility• Local area around Montreal and Florence
G3: Intervening context awareness• Relative positions, detours (interesting
places?)
G4: Distance awareness• Approximate trip distance
Related Work: Space Distortion
• Fisheye views– [Furnas 1986, Shoemaker 2007]
• Rubber sheet– [Sarkar 1993, Munzner 2003]
Related Work: Semantic Distortion
• DOITrees [Card 2002]• SpaceTree [Plaisant 2002]
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Space-folding using Mélange
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Basic Idea
Visualizing Folds
open fold page
mouse cursor
closed fold pagesfocus A focus B
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Implementation
• Java platform built using OpenGL– JOGL bindings
• Scene graph w/ geometrical shapes– Arcs, circles, rectangles (textured), etc
• Focus points (one primary) controlled by user and/or application
• Mélange canvas guarantees visibility– Seamlessly splits shapes into subshapes
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Evaluation
Evaluation - Overview
• Controlled Experiment• Based on social networks analysis:
compare the immediate context of two distant connected nodes
MatLink: social network analysis using matrices[Henry&Fekete @ Interact 2007]
Evaluation - Overview
• Controlled Experiment• Based on social networks analysis:
compare the immediate context of two distant connected nodes
MatLink: social network analysis using matrices[Henry&Fekete @ Interact 2007]
Evaluation - Overview
• Controlled Experiment• Based on social networks analysis:
compare the immediate context of two distant connected nodes
MatLink: social network analysis using matrices[Henry&Fekete @ Interact 2007]
Evaluation - Overview
• Controlled Experiment• Based on social networks analysis:
compare the immediate context of two distant connected nodes
MatLink: social network analysis using matrices[Henry&Fekete @ Interact 2007]
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Evaluation - Overview
• 1 trial consisted in 3 tasks– (T1) Find the connected twin of the source node– (T2) Estimate the distance between the two nodes– (T3) Estimate the number of contextual features
Connected Twin Node
Distractor Nodes
Source Node
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Evaluation - Overview
• 1 trial consisted in 3 tasks– (T1) Find the connected twin of the source node– (T2) Estimate the distance between the two nodes– (T3) Estimate the number of contextual features
1 Screen
Target NodeContextual Features
Source Node
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Evaluation - Factors
• 3x3x2x2 within-subject design• 3 Presentation techniques, interaction with PZ
– Single Viewport (SV)– Split-Screen Viewport (SSV)– Melange (M)
• 3 Off-Screen Distance: 4, 8 or 16 screens(distance between the two nodes)
• 2 Distractor density: low or high (1 or 2 per screen)(number of false targets between the two nodes)
• 2 Contextual Features density: few (≤5) many (>5)(number of contextual features between the two nodes)
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Evaluation - Hypotheses
• Mélange’s presentation of context does not interfere with navigation
• Mélange’s presentation of context provides significant improvement to:– Distance awareness– Contextual features awareness
Evaluation – Results Outline• Time
– Finding the twin of the source node (T1)No significant difference in completion time between techniques
– Estimating distance between the nodes (T2)Mélange is significantly faster than both Single Viewport and Split Screen Viewport (F2,22 = 8.695, p ≤.05)
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Evaluation – Results Outline• Time
– Finding the twin of the source node (T1)No significant difference in completion time between techniques
– Estimating distance between the nodes (T2)Mélange is significantly faster than both Single Viewport and Split Screen Viewport (F2,22 = 8.695, p ≤.05)
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Evaluation – Results Outline• Time
– Finding the twin of the source node (T1)No significant difference in completion time between techniques
– Estimating distance between the nodes (T2)Mélange is significantly faster than both Single Viewport and Split Screen Viewport (F2,22 = 8.695, p ≤.05)
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Evaluation – Results Outline• Time
– Finding the twin of the source node (T1)No significant difference in completion time between techniques
– Estimating distance between the nodes (T2)Mélange is significantly faster than both Single Viewport and Split Screen Viewport (F2,22 = 8.695, p ≤.05)
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Time T2 + Time T3
F2,22=9.855, p<0.001.
Evaluation – Results Outline• Correctness
– Estimating distance between the nodes (T2)Mélange is significantly better than Split Screen Viewport and similar to Single Viewport
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Results Summary
• Mélange provides– G1: Guaranteed focus visibility– G2: Surrounding context visibility
• Mélange is significantly more efficient in supporting contextual tasks– G3: Intervening context awareness– G4: Distance awareness
• Mélange is not slower than the other techniques for navigation
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Conclusions and Future Work• Presentation technique for
supporting multi-focus interaction• Folds 2D space into 3D to guarantee
visibility of focus points• Evaluation shows significant
improvement over state of the art
• Future: Interaction for large spaces, real-world applications
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Questions?
• Contacts (@lri.fr):Niklas Elmqvist – elmNathalie Henry – nhenryYann Riche – richeJean-Daniel Fekete – fekete
Project website: http://www.lri.fr/~elm/projects/melange.html
Thanks to our drummer, Pierre
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Related Work
Technique G1 G2 G3 G4
Zoom and pan[Appert 2006, Igarashi 2000] - - - -
Split-screen[Shoemaker 2007]
Y Y - -
Fisheye views[Furnas 1986, Shoemaker 2007] Y P Y -
Rubber sheet[Sarkar 1993, Munzner 2007] P P Y P
Semantic distortion[Card 2002, Plaisant 2002] Y Y Y -