Gravity Navigation
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Transcript of Gravity Navigation
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GravNav: Using a Gravity Model for Multi-Scale Navigation
Waqas Javed, Sohaib Ghani, Niklas ElmqvistPurdue UniversityWest Lafayette, IN
USA
Presented By: Waqas Javed
AVI 2012May 21-24, 2012 ▪ Capri Island, Italy
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Lafayette
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Lafayette
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D. Fisher. Hotmap: Looking at geographic attention. IEEE Transactions on Visualization and Computer Graphics, 13(6):1184–1191, 2007.
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Gravity Navigation
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Related Work
• General and Multi-scale Navigation– Pan and zoom (Furnas and Bederson 2005)– Speed-dependent automatic zooming (Igarashi and Hinckley 2000)– OrthoZoom (Appert and Fekete 2006)
• Assisted Navigation– Topology aware navigation (Moscovich et al. 2009, Ghani et al. 2011)– Content aware scrolling (Ishak and Feiner 2006)
• Pointing– Semantic pointing (Blanch et al. 2004)– Sticky targets (Mandryk and Gutwin 2008)– Force-enhanced targets (Ahlström et al. 2006)
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Degree of Interest in Gravity Navigation
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Degree of Interest
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Gravity Model• Attention gravity vector
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Motor Space Model
• Using the attention gravity vector to manipulate the control display (CD) mapping– CD gain– CD direction
• Gravity panning• Gravity zooming
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User Study
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Task
• Zoomed-out overview to a zoomed-in detail view of a particular target
• The target was surrounded by distractor objects• 2xN distractor objects at a random position on the
periphery of every Nth imaginary circle• The target was a square the size of 10% of the viewport
size at 1:1 zoom factor• The square was red whenever viewed at less than full
scale factor, and blue otherwise• A collection of successively larger concentric rings
centered around the target
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Task Video
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Study Factors
• Navigation Technique (T)• Zoom Control Technique (Z)• Index of Difficulty (ID)
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Study Factors
• Navigation Technique (T)– Standard navigation (SN)– Gravity navigation (GN)
• Zoom Control Technique (Z)• Index of Difficulty (ID)
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Study Factors
• Navigation Technique (T)• Zoom Control Technique (Z)– Standard zoom control (SZ)– OrthoZoom (OZ)
• Index of Difficulty (ID)
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Study Factors
• Navigation Technique (T)• Zoom Control Technique (Z)• Index of Difficulty (ID)
– 5 different ID values (10, 15, 20, 25, and 30)
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Experimental Design
• Participants: 12 • Navigation Technique T: 2– SN (Standard Navigation)– GN (Gravity Navigation)
• Zoom Control Technique Z: 2– SZ (Standard Zoom Control)– OZ (OrthoZoom)
• Index of Difficulty ID: 5– 10, 15, 20, 25, 30
• Repetitions: 5
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Experimental Design
• Trials were organized in blocks based on zoom control technique Z
• Within each block T and ID factors were randomized
• Measures during each trial– completion time – cinematic interaction data
• Minimum five training tasks
Experimental Hypothesis
• H1: GN will be faster than SN• H2: OZ will be faster than SZ• H3: GN will benefit more from OZ than SN
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Experimental Results
• Completion Time• Navigation Behavior• Subjective Feedback
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Completion Time
Factor Significant Effect
Navigation Technique
Zoom Control Technique
Index of Difficulty
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Completion Time
• GN was an average of 25.6% faster than SN
GN + OZ
1Fastest GN + SZ
2 SN + OZ
3 SN + SZ
4Slowest
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Navigation Behavior
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Subjective Feedback
• Participants were generally favorable in regards to OrthoZoom
• Few participants felt that they often overshot the target with OrthoZoom– “the [OrthoZoom] task sometimes got out of control.”
• A couple of participants stated that some trials were easier than others – “sometimes it felt as if my cursor snapped onto the target,
whereas other times not so much.”– Another thought that targets seemed to “pull in the cursor.”
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Summary of Results
• Gravity navigation exhibited significantly faster completion times than standard navigation (confirming H1)
• Variable-rate zoom control using OrthoZoom resulted in significantly faster completion times than standard constant rate zoom control (confirming H2)
• Gravity navigation with OrthoZoom was significantly faster than gravity navigation with constant-rate zoom control whereas no significant such difference was found for standard navigation (confirming H3)
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Conclusion
• A novel family of multi-scale navigation techniques that we call GravNav
• GravNav utilizes the topology of the underlying visual space to assist navigation
• Quantitative evaluation of the GravNav technique
• Study results confirm the usefulness of the new technique
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Thank You!
Contact Information:Waqas JavedSchool of Electrical & Computer EngineeringPurdue UniversityWest Lafayette, IN, USA
E-mail: [email protected]
http://engineering.purdue.edu/pivot/
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