Title: Immersive Experiences for Team Training
1Immersive Experiences for Team Training
- PROPOSAL FOR AN NSF SCIENCE AND TECHNOLOGY CENTER
- JUNE 2005-JUNE 2010-JUNE 2015
- 5.2 M/YEAR (including matching)
- UNC, UCF, Morehouse Medical College
- Will know March, 2005
2Our Vision for Capability
3The Goal
- Whole team in one space
- See, touch, talk to each other
- Personal synthetic stereo view of VE, with some
real objects - No encumbrances beyond sunglasses
4Todays VEs for Team Training
- Superbly successful for vehicle drivers
- Everything reachable is real
- Everything virtual is out-the-window
- User is unencumbered
- Fine for groups sharing one viewpoint
- Pretty good for some solo training
- Quite poor for teams with individual viewpoints
5Four Thrusts of the Center
- Training science
- University of Central Florida
- Radical immersive environments
- Collaboration with real trainers
- Morehouse College of Medicine
- UNC Trauma Surgery, Emerg Medicine
- U.S. Coast Guard Trg. Facil. Yorktown
- U-Drive-It Facility to change practice
6Our Vision for Immersive Display
- Five-year
- CAVE-like
- but ceiling projectors
- 4 eyes, then 8 eyes with individual images
- Ten-year
- Full autostereoscopic for 8 eyes
- Lots of pixels on the walls
- Flys-eye lenses
7Our Vision for Image Generation
- Five-year
- PC cluster with graphics cards
- Ten-year
- New light-field rendering architecture
- 4-D frame buffer all views from one rendering
8Our Vision for Tracking
- Wide-area full-body tracking
- Tracking of tools as well as people
- Many approachesnet will be hybrid
- New theoretical approach for design
- Obviate head-tracking
- Acoustic spread-spectrum tracker
- Video tracking with sub-imposed skeletal models
9Our Vision for Scenario Generation
- FAA System enhanced with branching
- Model acquisition by laser and video
- Scenario capture by computer vision
- First in UNC Emergency Room
- Next at USCG TF Yorktown
- Next in streets of Atlanta
10Our Vision for Interaction
- Mixed real and virtual
- Objects
- People (autonomous agents)
- Collision detection
- Proper physical responses
- Novel interaction techniques
- Imperceptible redirectionwalking, hand
- Passive haptics (e.g., ledge floor in pit)
11Redirected Walking Razzaque
Blue perceived path Red actual path
12Basic VE Science Questions
- What is an effective VE?
- How can we measure effectiveness?
- What makes a VE effective?
- Can VEs effectively train small teams?
13Our Vision for Basic Science of VEs
- Measure effectiveness of the illusions
- Physiological measures of stress
- Behavioral measures
- Subjective measures
- Training and training transfer measures
14Physiological Measures Stress
15Some ResultsHigh-Order Bits
- We can measure how scared you get
- Really walking really matters
- Latency really matters
- Frame-rate matters up to 30 fps
- Global illumination gt Local
- 3-D sound seems no better than 2-D
- Touching something gtgt touching nothing