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Input Devices
CS160: User Interfaces
John Canny
Reminders
Midterm is next Weds.
Sample midterms are online, with solutions.
Review session in class on Monday, also go to
discussion sections this week.
Reminders
Next project checkpoint (interactive prototype)
assignment is out, due 11/5/12.
PA III is out, due 10/29/12. Uses CometD, but server
code is provided.
Input Devices: Important Tasks
• Text Entry
• Pointing/Marking
– Target acquisition
– Steering / positioning
– Freehand drawing
– Drawing lines
– Tracing and digitizing
– …
• Voice: like text entry but limited
– better to be “dialogic”
• Array of Discrete Inputs
• Many variants of form and key layout
– Can be one-handed or two
– Wide range of sizes
– Two-hand full keyboard is relatively standardized, Less standardization on others: Command keys, generic function keys, cursor movement, numeric keypad,...
• Use procedural memory
– Power law of practice
Text Entry: Keystroke Devices
5
1a
nT T n c
Keyboards
Ergonomics
Ergonomics
Key Layouts
Mobile Text Entry: Keypads
11
• Multi-tap mappings
– Multiple presses per letter
• Ambiguity resolution
– One press per letter, dictionary lookup
Mobile Text Entry: Keypads
12
• Chording
– Multiple keys pressed
simultaneously
– (n choose 4)
combinations = 495
• Can use for words!
– Use fewer keys for
common words
– Covers perhaps 80% of
typical words.
Twiddler2, HandyKey
Mobile Text Entry: Touch / Stylus
Soft Keyboards
• Benefits?
Drawbacks?
Mactoids.com
Mobile Text Entry: Handwriting
Recog.
Mobile Text Entry: Touch / Stylus
• Custom symbol sets
• Graffiti
• improve recognition accuracy; appropriate for indirect (eyes-free) input
Mobile Text Entry: Touch / Stylus
• Stroke Entry Methods (e.g., Swype, ShapeWriter)
Which is fastest?
Beyond text input…
• Even with keyboards, there is more information gathered
than the text.
• Every person types differently: characters are grouped
together into “chunks” in different ways.
• Biometrics: you can partially identify a person from the
timing of their keystrokes. e.g. timing of password typing has
shown accuracies as high as 99%:
Novelty Detection Approach for Keystroke Dynamics Identity
Verification, Enzhe Yu and Sungzoon Cho, Intelligent Data Engineering and
Automated Learning Lecture Notes in Computer Science, 2003, Volume
2690/2003
What about Speech Recognition?
• Dictation is faster than typing (~100 wpm)
What about Speech Recognition?
• Dictation is faster than typing (~100 wpm), BUT:
– Speech is different from written language:
Speaking in well-formed, complete, print-ready sentences
is cognitively challenging
– High cost of correcting errors through speech channel
alone
– Social awkwardness?
• Then came Siri, and…
AT&T Watson service
Pointing Devices
22
(cc) Flickr photo by Mike fj40
Mouse. Engelbart and English ~1964
Source: Card, Stu. Lecture on Human Information Interaction. Stanford, 2007.
24
IR emitter IR detector slotted wheel
(between emitter & detector)
Uses two out-of-phase detectors
25
High
High
26
Optical mice
In effect use computer vision with a tiny image sensor.
Optical mice
Use computer vision with a tiny image sensor.
Other device properties:
• Indirect vs. Direct
– Direct: Input and output space are unified
• C:D Ratio
– For one unit of movement in physical space, how far does
the cursor travel in display space?
– Q: What is the C:D ratio for direct touch screen input?
• Device Acquisition Time
30
Trackball, Trackpad
31
Trackpoint
• Indirect, force sensing, velocity control
• Nonlinear transfer function
Force
Velo
city
(cc) Image by flickr user tsaiid
Mobile Pointing
• D-Pad (see: arrow keys)
• Trackball
• Direct touch (see: Trackpad)
• Stylus
What else can you detect with a Mouse?
33
What else can you detect with a Mouse?
Stress affects muscle tension, which will change the dynamics of
mouse movements. Analyze “reference” movements
34
MouStress
Analyze the arm/hand as a simple second-order mechanical
system, and find two poles using LPC.
Actual tasks were pointing and dragging on variably-spaced
targets:
35
MouStress
Phases of the tests:
36
MouStress
Mouse dynamic tests (mCalm and mStress states)
p < 0.002 p < 0.002
37
MouStress
Mouse sensing was able to reliably distinguish the
calm and stress states, even when standard measures
(Heart-Rate Variability) were not.
i.e. it appeared to be even more sensitive than the
best existing biometric measure.
38
Next steps
Analyze arm/hand dynamics while holding a cell phone, and
performing screen gestures.
Several different dynamic modes,…
Impulse gestures (tapping) and dragging,…
39
Everything is best for something and worst for something else.
- Bill Buxton
Multi-Touch: Strengths
• Direct input allows maximal screen space for mobile devices (ocular centrism).
• More degrees of freedom.
• “Virtual input devices” are adaptable.
• No extra pieces to lose or break (styli!)
Challenges
• No tactile feedback.
• Requires free use of (both) hands and eyes.
• “Fat Finger” problems – precision & occlusion
The “Fat Finger” Problem
touch
Graphics: Patrick Baudisch, nanoTouch
A Software Solution
Graphics: D. Vogel, P. Baudisch - Shift
A Hardware Solution: Use the Backside
touch
pointer
Graphics: Patrick Baudisch, nanoTouch
Terminology
• Touch-tablets vs Touch screens
• Single-finger vs multi-finger
• Multi-person vs multi-touch
• Points vs Postures
• Hands and fingers vs Objects
(from Buxton)
Wobbrock, J., Morris, M.R., and Wilson, A. User-Defined Gestures for Surface Computing. Proceedings of CHI 2009, 1083-1092.
Multi-point Gestures
Posture-based Interaction
Golan Levin, Zach Lieberman – The Manual Input Sessions Workstation
Hybrids: Keyboards on Interactive Tables
http://www.youtube.com/watch?v=qIASBXG3-Sk
B. Hartmann, M. Morris, H. Benko, A. Wilson: Augmenting
Interactive Surfaces With Keyboards and Mice. UIST 2009
Hybrids: Multi-touch on Mice
Mouse 2.0: Multi-touch Meets the Mouse
Nicolas Villar, Shahram Izadi, Dan Rosenfeld, Hrvoje Benko, John Helmes, Jonathan Westhues, Steve Hodges,
Eyal Ofek, Alex Butler, Xiang Cao and Billy Chen.
Proceedings of UIST 2009.
Input modes for Tablets
• Accelerometer (usually), gyroscope, compass
(sometimes) move the tablet as input (Holotoy)
• Camera: track head, eyes, limbs move yourself,
OpenCV toolkit (Computer Vision).
Microsoft Kinect
• Huge number of applications in games etc.
• Fast calculation of body skeleton supports easy
recognition of gestures.
• Some very compelling special
apps, e.g. in surgery
Skinput
http://www.youtube.com/watch?v=g3XPUdW9Ryg
Skinput
Humantenna
http://www.youtube.com/watch?v=7lRnm2oFGdc
Humantenna
Summary
Keyboards, mice, touchscreens, speech. But lots of
innovations:
• Rich gesture vocabulary
• Using local context
• Dialogicality
• Secondary cues: identity, stress, emotion
New input modes:
• 3D remote sensing (Kinect)
• Body sensing
• RF environment sensing
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