Leveraging Human Capabilities in Perceptual Interfaces - PowerPoint PPT Presentation

1 / 58
About This Presentation
Title:

Leveraging Human Capabilities in Perceptual Interfaces

Description:

Leveraging Human Capabilities in Perceptual Interfaces George G. Robertson Microsoft Research – PowerPoint PPT presentation

Number of Views:137
Avg rating:3.0/5.0
Slides: 59
Provided by: Georg352
Category:

less

Transcript and Presenter's Notes

Title: Leveraging Human Capabilities in Perceptual Interfaces


1
Leveraging Human CapabilitiesinPerceptual
Interfaces
  • George G. Robertson
  • Microsoft Research

2
Outline and Goal
  • What are perceptual interfaces?
  • Perceptive vs perceptual
  • Multimodal interfaces
  • Challenge Do our interfaces work?
  • How do we find out?
  • Challenge Broaden our scope
  • Leverage other natural human capabilities

3
Perceptive to Perceptual
  • Perceptive UI aware of user
  • Input to computer use human motor skills
  • Multimodal UI use communication skills
  • We use multiple modalities to communicate
  • Perceptual UI use many human abilities
  • Perception, cognition, motor, communication

4
What are Modalities?
Sensations (hearing or seeing)
Human communication channels
5
What are Multimodal Interfaces?
  • Attempts to use human communication skills
  • Provide user with multiple modalities
  • May be simultaneous or not
  • Fusion vs Temporal Constraints
  • Multiple styles of interaction

6
Examples
  • Bolt, SIGGRAPH80
  • Put That There
  • Speech and gestures used simultaneously

7
Put That There
8
Examples (continued)
  • Buxton and Myers, CHI86
  • Two-handed input
  • Cohen et al, CHI89
  • Direct manipulation and NL
  • Hauptmann, CHI89
  • Speech and gestures

9
Examples (continued)
  • Bolt, UIST92
  • Two-handed gestures and Gaze
  • Blattner Dannenberg, 1992 book
  • Hanne text gestures (interaction styles)
  • Pausch selection by multimodal input
  • Rudnicky speech, gesture, keyboard
  • Bier et al, SIGGRAPH93
  • Tool Glass two-handed input

10
Examples (continued)
  • Balboa Coutaz, Intelligent UI93
  • Taxonomy and evaluation of MMUI
  • Walker, CHI94
  • Facial expression (multimodal output)
  • Nigay Coutaz, CHI95
  • Architecture for fused multimodal input

11
Why Multimodal Interfaces?
  • Now fall far short of human capabilities
  • Higher bandwidth is possible
  • Different modalities excel at different tasks
  • Errors and disfluencies reduced
  • Multimodal interfaces are more engaging

12
Leverage Human Capabilities
  • Leverage senses and perceptual system
  • Users perceive multiple things at once
  • Leverage motor and effector capabilities
  • Users do multiple things at once

13
Senses and Perception
  • Use more of users senses
  • Not just vision
  • Sound
  • Tactile feedback
  • Taste and smell (maybe in the future)
  • Users perceive multiple things at once
  • e.g., vision and sound

14
Motor Effector Capabilities
  • Currently pointing or typing
  • Much more is possible
  • Gesture input
  • Two-handed input
  • Speech and NL
  • Body position, orientation, and gaze
  • Users do multiple things at once
  • e.g., speak and use hand gestures

15
Simultaneous Modalities?
  • Single modality at a time
  • Adapt to display characteristics
  • Let user determine input mode
  • Redundant, but only one at a time
  • Multiple simultaneous modalities
  • Two-handed input
  • Speech and hand gestures
  • Graphics and sound

16
Taxonomy (Balboa, 1993)
Fusion
Put that there click click
Put that click there click
Synergetic
multiple menu selection or multiple spoken
commands
Shortcuts
Exclusive
Temporal Constraints
Independent
Sequential
Concurrent
17
Modality Style of Interaction
  • Many styles exist
  • Command interface
  • NL
  • Direct manipulation (WIMP and non-WIMP)
  • Conversational (with an interface agent)
  • Collaborative
  • Mixed styles produce multimodal UI
  • Direct manipulation and conversational agent

18
Multimodal versus Multimedia
  • Multimedia is about media channels
  • Text, graphics, animation, video all visual
    media
  • Multimodal is about sensory modalities
  • Visual, auditory, tactile,
  • Multimedia is a subset of Multimodal Output

19
How Do The Pieces Fit?
Perceptual UI
Multimodal Input
Multimodal Output
Multimedia
Perceptive UI
20
Challenge
  • Do our interfaces actually work?
  • How do we find out?

21
Why Test For Usability?
  • Commercial efforts require proof
  • Cost benefit analysis before investment
  • Intuitions are great for design
  • But intuition is not always right!
  • Peripheral Lens

22
Peripheral Vision
  • Does peripheral vision make navigation easier?
  • Can we simulate peripheral vision?

23
A Virtual Hallway
24
Peripheral Lenses
25
Peripheral Lens
26
Peripheral Lens Intuitions
  • Locomotion should be easier
  • Especially around corners
  • Wayfinding should be easier
  • You can see far sooner

27
Peripheral Lens Findings
  • Lenses were about the same speed
  • Harder to use for inexperienced people
  • Corner turning was not faster

28
The Lesson
  • Do not rely solely on intuition
  • Test for usability!

29
Challenge
  • Are we fully using human capabilities?
  • Peceptive UI is aware of the body
  • Multimodal UI is aware the we use multiple
    modalities, sometimes simultaneous
  • Perceptual UI should go beyond both of these

30
Research Strategy
Exploit Technology Discontinuities
Leverage Human Capabilities
Compelling Task Information Access
31
Engaging Human Abilities
communication
perceptual
motor
cognitive
  • understand complexity
  • new classes of tasks
  • less effort

Helps User
32
Examples Communication
  • Language
  • Gesture
  • Awareness
  • Emotion
  • Multimodal
  • Flexible
  • Robust
  • Dialogue to resolve ambiguity

33
Examples Communication
  • Language
  • Gesture
  • Awareness
  • Emotion
  • Multimodal
  • Hands
  • Body pose
  • Facial expression

34
Camera-BasedConversational Interfaces
  • Leverage face to face communication skills

35
Examples Communication
  • Language
  • Gesture
  • Awareness
  • Emotion
  • Multimodal
  • Is anybody there?
  • Doing what?

36
Camera-Based Awareness
  • What is the user doing?

37
Examples Communication
  • Language
  • Gesture
  • Awareness
  • Emotion
  • Multimodal
  • Social response
  • Perceived personality

38
Examples Communication
  • Language
  • Gesture
  • Awareness
  • Emotion
  • Multimodal
  • Natural
  • Choice
  • Reduces errors
  • Higher bandwidth

39
Examples Motor Skills
  • Bimanual skills
  • Muscle memory
  • Multimodal Map Manipulation
  • Two hands
  • Speech

40
Camera-Based Navigation
  • How do our bodies move when we navigate?

41
Examples Perception
  • Spatial relationships
  • Pattern recognition
  • Object constancy
  • Parallax
  • Other Senses

Cone Tree Xerox PARC Information Visualizer
42
Cone Tree
43
Examples Perception
  • Spatial relationships
  • Pattern recognition
  • Object constancy
  • Parallax
  • Other Senses
  • Key 3D depth cue
  • Sensor issues
  • Camera-based head-motion parallax

44
Camera-Based Head-Motion Parallax
  • Motion parallax is one of strongest 3D depth cues

45
Examples Perception
  • Spatial relationships
  • Pattern recognition
  • Object constancy
  • Parallax
  • Other Senses
  • Auditory
  • Tactile
  • Kinesthetic
  • Vestibular
  • Taste
  • Olfactory

46
Examples Perception Olfactory? Maybe soon?
Ferris Productions Olfactory VR Add-on Time,
April 29, 1996
Barfield Danas Olfactory Displays Presence,
Winter, 1995
47
Examples Cognition
  • Spatial memory
  • Cognitive chunking
  • Attention
  • Curiosity
  • Time Constants

Data Mountain
48
Data Mountain
  • Favorites Management
  • Exploits
  • Spatial memory
  • 3D perception
  • Pattern recognition
  • Advantages
  • Spatial organization
  • Not page at a time
  • 3D advantages with 2D interaction

49
Sample User Reaction
Strongest cue ... relative size
Subject Layout of 100 Pages
50
VIDEO
51
Data Mountain Usability
  • Spatial memory works in virtual environments!
  • 26 faster than IE4 Favorites
  • 2x faster with Implicit Query

52
Implicit Query Visualization
  • Highlight related pages
  • Slightly slower for storage
  • Over 2x faster for retrieval

53
Examples Cognition
  • Spatial memory
  • Cognitive chunking
  • Attention
  • Curiosity
  • Time Constants

Navigate Map
Zoom
Pan
dX
dY
factor
Center
X
Y
54
Examples Cognition
  • Spatial memory
  • Cognitive chunking
  • Attention
  • Curiosity
  • Time Constants
  • Motion attracts
  • Animate with care
  • Peripheral vision
  • HMD vs desktop
  • Focus in Context

55
Focus in Context
56
Examples Cognition
  • Spatial memory
  • Cognitive chunking
  • Attention
  • Curiosity
  • Time Constants
  • Discoverability
  • Fear
  • Universal Undo

57
Examples Cognition
  • Spatial memory
  • Cognitive chunking
  • Attention
  • Curiosity
  • Time Constants

(sec)
100
Unit Cognitive Task
10
1
Immediate Response
0.1
Animation
58
Summary Recommendations
  • Broaden scope!
  • Identify and engage human abilities
  • Go beyond the perceptive and multimodal
  • Test for usability!
Write a Comment
User Comments (0)
About PowerShow.com