move to improve: promoting physical navigation to increase user performance with large displays
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Move to Improve: Promoting Physical Navigation to Increase User Performance with Large Displays. Robert Ball Virginia Tech November 10, 2006. Motivation: Cuban Missile Crisis: September/October 1962. U-2 Spy plane takes high-resolution pictures of parts of Cuba - PowerPoint PPT PresentationTRANSCRIPT
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Move to Improve: Promoting Physical Navigation to Increase User Performance with Large Displays
Robert BallVirginia TechNovember 10, 2006
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Motivation: Cuban Missile Crisis: September/October 1962
U-2 Spy plane takes high-resolutionpictures of parts of Cubahttp://www.gwu.edu/~nsarchiv/nsa/cuba_mis_cri/1.jpg
Picture taken of SA-2 missile construction sitehttp://www.gwu.edu/~nsarchiv/nsa/cuba_mis_cri/1.jpg
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Analysis of pictures
U-2 Spy place takes high-resolution pictures. Analyst must
interpret pictureswith this:
Why: physical navigation
Inside the CIA’s National PhotographicInterpretation Center (NPIC), Washington D.C., 1962. http://www.gwu.edu/~nsarchiv/nsa/cuba_mis_cri/7.jpg
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Related Work
Games!
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Related work – other domains and applications
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Physical navigation related workHMDHead-mounted display
CAVE
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Experiment Motivation
Research Questions: Do users prefer physical navigation with
large, high-resolution displays? Why? If so, does this result in improved user
performance? Is physical navigation truly more beneficial
than virtual navigation in terms of performance time?
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Experimental Design – data and visualization 3,500 houses for sale in Houston, TX Semantic zooming scheme, zooming only resulted in
more information being displayed.
To see all of the houses with all the details shown would require about a 100-monitor display.
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Experimental Design – display, interaction, and tracking 24 tiled monitors
Wireless mouse Vicon system
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Experimental Design – tasks
4 tasks: Navigation Search Pattern finding Insight finding
Insight task: Used paper, pen, and stand. No correct answers.
Other tasks: Walked and spoke answer. Only one correct answer.
Within-subject design
Between-subject design
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Experiment results - performance
2-way ANOVA: main effects fordisplay width (F(1,1324)=20.56, p<0.01) task type (F(2,1324)=77.05, p<0.01)
Tukey HSD analysis showed different task types were all in different groups, so:
TaskMain effect of display width
navigation (F(1,508) = 118.9, p<0.01)
search (F(1, 762) = 38.18, p<0.01)
pattern finding (F(1, 90) = 3.53, p=0.06)
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Experiment results – performance, cont.
Performance Times
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8
Display width (in number of columns)
Pe
rfo
rma
nce
tim
e (
s)
Navigation Search
TaskMain effect of display width
navigation (F(1,508) = 118.9, p<0.01)
search (F(1, 762) = 38.18, p<0.01)
pattern finding (F(1, 90) = 3.53, p=0.06)
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Experiment results - Performance
We found no significant results based on the level of insight for the fourth task.
So, we focus on results for the first three tasks in this section.
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Virtual Navigation Analysis – zooms 2-way ANOVA: main effects for
task type (F(3,1400)=416.2, p<0.01)display width (F(1,1400)=34.8, p<0.01)near-significant interaction of task type and
display width (F(3,1400)=2.4, p=0.06).
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Virtual Navigation Analysis – zooms per task
Tasks - MetricsMain effect of display width
navigation - zooms (F(1,508)= 144.6, p<0.01)
navigation - panning not significant
search - zooms (F(1,762) =114.1, p<0.01)
search - panning (F(1,762) = 26.7, p<0.01)
pattern - zooms not significant
pattern - panning (F(1,90) = 7.8, p<0.01)
Number of zooms
0
5
10
15
20
25
1 2 3 4 5 6 7 8
Display width (in number of columns)
Nu
mb
er
of z
oo
ms
Navigation Search Pattern
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Virtual Navigation Analysis – pans
2-way ANOVA: main effects for task type (F(3,1400)=301.3, p<0.01)display width (F(1,1400)=63.86, p<0.01) interaction of task type and display width
(F(3,1400)=17.22, p<0.01).
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Virtual Navigation Analysis – pans per task
Tasks - MetricsMain effect of display width
navigation - zooms (F(1,508)= 144.6, p<0.01)
navigation - panning not significant
search - zooms (F(1,762) =114.1, p<0.01)
search - panning (F(1,762) = 26.7, p<0.01)
pattern - zooms not significant
pattern - panning (F(1,90) = 7.8, p<0.01)
Number of pans - navigation and search tasks
0
50
100
150
200
1 2 3 4 5 6 7 8
Display width (in number of columns)
Nu
mb
er
of p
an
s
Navigation Search
Number of pans - pattern task
0
200
400
600
800
1000
1200
1 2 3 4 5 6 7 8
Display width (in number of columns)
Nu
mb
er
of p
an
s
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Physical Navigation Analysis
Douglas-Peucker algorithm used to guarantee that what we were analyzing was actual movement - not jitter.
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Physical Navigation Analysis, cont.
2-way ANOVA for total X distance: main effects for task type (F(3,1400)=75.1, p<0.01)display width (F(1,1400)=24.1, p<0.01) interaction of task type and display width
(F(3,1400)=4.0, p<0.01)
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Physical Navigation Analysis – per task
Task Main effect of display width
navigation not significant
search (F(1,762) = 4.52, p=0.03)
pattern finding (F(1,84) = 16.62, p<0.01)
Total Distance in the X Direction - search task
020406080
100120
1 2 3 4 5 6 7 8
Display width(in number of columns)
Mo
vem
en
t in
inch
es
.
Total Distance in the X Direction - pattern task
0
100
200300
400
500
1 2 3 4 5 6 7 8
Display width(in number of columns)
Mo
vem
en
t in
inch
es
.
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Visualization of physical movement
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Experiment conclusions
Do users prefer physical navigation with large, high-resolution displays?
YES
When faced with a choice of physical or virtual navigation, 100% of the participants
chose only to physically navigate.
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Experiment conclusions
If so, does this result in improved user performance?
YESPerformance Times
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8
Display width (in number of columns)
Pe
rfo
rma
nce
tim
e (
s)
Navigation Search
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Experiment conclusions
Is physical navigation truly more beneficial than virtual navigation in terms of performance time?
YES
Virtual navigation has a greater negative correlation on performance than physical navigation. The number of zooms correlated with performance with a
correlation coefficient of 0.69. The number of pans correlated with performance with a
correlation coefficient of 0.68. However, physical distance traveled did not significantly
correlate with performance.
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Future work
Do the results from this study extrapolate to 3D data? To non-geospatial data?
How does fatigue/longitudinal use of such displays affect the results of this experiment?