Transcript CS376 Introduction - Stanford University

stanford hci group / cs376
Gestural / Bimanual
Input
Scott Klemmer
29 November
2005
research topics in human-computer interaction
Final project papers &
presentations
 Final papers: 4 pages in the
traditional CHI format or 6
pages in the work-in-progress
format (same effective length,
I suggest the latter as you
can submit it to CHI WIP)
 Final presentations: 4 minutes
each, followed by
posters/demos
Gestural / Bimanual Input
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How to write a good
paper
 Have a clear hypothesis
 Explain design ideas, system,
and eval
 Read your critiques of earlier
work
 Compare your results to 4-5
pieces of related work
 scholar.google.com is a great
resource
Gestural / Bimanual Input
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Milestone 2 demo times
1:30 - Deepak Kumar and David Tu
1:40 - David Akers
1:50 - Luping May, Kevin Collins, Scott Doorley
2:00 - Malte F. Jung, Howard Kao, Ravi Teja
Tiruvury, Parul Vora
2:10 - Becky Currano and Murad Akhter
2:20 - Christina Chan
2:30 - Tom Hurlbutt
2:40 - Dhyanesh Narayanan
2:50 - BREAK
3:00 - Dean Eckles, Tony Tulathimutte, Tanya
Breshears
3:10 - Jonathan Effrat and May Tan
3:20 - Shailendra Rao and Abhay Sukumaran
3:30 - Adam Kahn and Doug Wightman
3:40 - Brandon Burr
3:50 - Angela Kessell
Chris
Gestural /and
Bimanual
Input Chan
4
Pointing Device
Evaluation
 Real task: interacting with GUI’s
 pointing is fundamental
 Experimental task: target acquisition
 abstract, elementary, essential
W
D
Gestural / Bimanual Input
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Fitts’ Law (Paul Fitts,
D
1954)MT  a  b log2 (  1)
W
Index of Difficulty (ID )
Task difficulty is analogous to information - execution
interpreted as human rate of information processing
Index of Performance (IP ) = ID/MT (bits/s)
Bandwidth
Throughput
W
D
Gestural / Bimanual Input
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50 years of data
Device
Hand
Mouse
Joystick
Trackball
Touchpad
Eyetracker
Study
IP (bits/s)
Fitts (1954)
10.6
Card, English, & Burr (1978)
10.4
Card, English, & Burr (1978)
5.0
Epps (1986)
2.9
Epps (1986)
1.6
Ware & Mikaelian (1987)
13.7
Reference:
MacKenzie, I. Fitts’ Law as a research and design tool in human computer
interaction. Human Computer Interaction, 1992, Vol. 7, pp. 91-139
Gestural / Bimanual Input
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What does Fitts’ law
really model?
Target Width
Veloci
ty
(c)
(a)
(b)
Distance
Gestural / Bimanual Input
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Using these law’s to
predict performance
Pop-up Linear Menu
Pop-up Pie Menu
Today
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Which will be faster on
average?
 pie menu Gestural
(bigger
& less
/ Bimanual targets
Input
9
Beyond pointing:
Trajectory based tasks
Gestural / Bimanual Input
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Gaming Fitts Law
 The Macintosh menu bar and
taskbar and the Windows XP
Taskbar have “infinite height”
improving their Fitts Law
performance
 …as does the back button in
the Firefox browser
Gestural / Bimanual Input
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Gestural / Bimanual Input
12
Yves Guiard: Kinematic
Chain
 Asymmetry in bimanual activities
 “Under standard conditions, the
spontaneous writing speed of
adults is reduced by some 20%
when instructions prevent the
non-preferred hand from
manipulating the page”
 Non-dominant hand (NDH) provides
a frame of reference for the
dominant hand (DH)
 NDH operates
at a course
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