1. 1 Transparent control of avatar gestures A prototype Francesca Barrientos GUIR Meeting  28 April 2000

2. 2 Review of interface elements Tracking (restricted) hand motion Free form Does not require watching the widget except to put down pen Facilitate proprioception Detect rests between gestures - calibration Design of mapping Qualitative control of motion No positional accuracy in output Does not require input accuracy

3. 3 Kinematic mapping New joint angle  Old joint angle + (  mouse position * scaling factor) For small movements, motion in horizontal plane Moving pen closer to self moves avatar hand closer to body

4. 4 Things that worked Within a small range, tracking is intuitive Can produce free form gestures Movement seems expressive Control is transparent

5. 5 Limitations Large motions not intuitive Hard to form gestures based on proximity to other parts of body Mapping may behave differently on different systems Limited range of motion Want hand to be somewhat independent Move one body part at a time

6. 6 Project goals Build a desktop VR system for controlling avatar gestures In particular for gesticulation Control by tracking a part of user’s body Study use of system Prove can perform some kinds of gesture not possible with other systems Understand which features contribute to communicative power of system

7. 7 Gesticulation Gesticulation is gesture that co- occurs with speech Meaning of the utterance is divided up between the words and gestures Gestures derive meaning from timing with respect to speech

8. 8 Main problems Limited input and complex output Control interface divides user’s attention

9. 9 Other solutions for nonverbal communication Discrete choices (menus) of expressions Usually affective (happy, sad, angry…) Usually facial Usually used with chat environments Examples: Emotion wheel in ComicChat Palace Gesture/Mimic panel in Vlnet

10. 10 Other solutions continued Analysis of text ComicChat uses keywords, acronyms, punctuation, etc. Semi-autonomous behaviors BodyChat by Vilhjálmsson Simple kinematic controls Sliders and similar widgets (e.g.. Slater) Full body motion capture

11. 11 Nonverbal communication function table (examples) AffectiveBlushing/ facial coloring None PossiblePhysiological sensor IllustratorHand motions/ describe shape of object or action YesHigh Continuous and inverse kinematics FunctionDisplay/features Speech timing IntentionAwarenessControl

12. 12 Nonverbal communication function table Function or form Display/features Speech timing IntentionAwarenessControl AffectiveMimics and postures/ lasting NoneHigh Discrete choices EmblemsSpecific hand shape NoneHigh Discrete choices Attention regulation Directed glancesNoneLow Discrete input/ Avatar agent Discourse marking Hand motions/ recognizable inflections YesHigh Continuous kinematic

13. 13 Where I fit in Forms and functions Emphasis and color Discourse marking Personality? Features Free form Co-occur with speech Intention and awareness User has voluntary control Continuous control

14. 14 Design informed by gesture research Stroke - most effortful phase Resting position part of prototype Space utilization Design/choice of mapping may be based on type of gesture Beats have favored direction and location Generation of beat gesture should be easily repeatable

15. 15 Next step 6DOF tracker input Track position of wrist in space instead of position on a plane Still designing kinematic mapping Proprioception Detect rest and preparation of gesture Independence of hand orientation Qualitative control Forward kinematic mapping

16. 16 And next Networked virtual environment User interface features Navigation Other gesture feedback (since user will have avatar point of view) User studies …

17. 17 Summary Presented a prototype gesture control system Reminded you of my research goals Suggested a framework for selecting controls suitable for different types of gestures Described how design is informed by gesture research Next steps

18. 18 Any questions?