1

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

2

Lafayette

3

Lafayette

4

D. Fisher. Hotmap: Looking at geographic attention. IEEE Transactions on Visualization and Computer Graphics, 13(6):1184–1191, 2007.

5

6

Gravity Navigation

7

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)

8

Degree of Interest in Gravity Navigation

9

Degree of Interest

10

Gravity Model• Attention gravity vector

11

Motor Space Model

• Using the attention gravity vector to manipulate the control display (CD) mapping– CD gain– CD direction

• Gravity panning• Gravity zooming

12

User Study

13

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

14

Task Video

15

Study Factors

• Navigation Technique (T)• Zoom Control Technique (Z)• Index of Difficulty (ID)

16

Study Factors

• Navigation Technique (T)– Standard navigation (SN)– Gravity navigation (GN)

• Zoom Control Technique (Z)• Index of Difficulty (ID)

17

Study Factors

• Navigation Technique (T)• Zoom Control Technique (Z)– Standard zoom control (SZ)– OrthoZoom (OZ)

• Index of Difficulty (ID)

18

Study Factors

• Navigation Technique (T)• Zoom Control Technique (Z)• Index of Difficulty (ID)

– 5 different ID values (10, 15, 20, 25, and 30)

19

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

20

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

21

22

Experimental Results

• Completion Time• Navigation Behavior• Subjective Feedback

23

Completion Time

Factor Significant Effect

Navigation Technique

Zoom Control Technique

Index of Difficulty

24

Completion Time

• GN was an average of 25.6% faster than SN

GN + OZ

1Fastest GN + SZ

2 SN + OZ

3 SN + SZ

4Slowest

25

Navigation Behavior

26

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.”

27

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)

28

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

29

Thank You!

Contact Information:Waqas JavedSchool of Electrical & Computer EngineeringPurdue UniversityWest Lafayette, IN, USA

E-mail: wjaved@purdue.edu

http://engineering.purdue.edu/pivot/

Questions???