1. VE Input Devices(I) Doug Bowman Virginia Tech Edited by Chang Song

2. (C) 2005 Doug Bowman, Virginia Tech2 Goals and Motivation Provide practical introduction to the input devices used in VEs Examine common and state of the art input devices look for general trends spark creativity Advantages and disadvantages Discuss how different input devices affect interface design

3. (C) 2005 Doug Bowman, Virginia Tech3 Input devices Hardware that allows the user to communicate with the system Input device vs. interaction technique Single device can implement many ITs

4. (C) 2005 Doug Bowman, Virginia Tech4 Human-computer interface System Software User interface software User Input devices Output devices ITs

5. (C) 2005 Doug Bowman, Virginia Tech5 Human-VE interface Tracking system Env. model Simulation loop: -render -check for events -respond to events -iterate simulation -get new tracker data Display(s) Input device(s)

6. (C) 2005 Doug Bowman, Virginia Tech6 Input device characteristics Degrees of Freedom (DOFs) & DOF composition (integral vs. separable) Range of reported values: discrete/continuous/hybrid User action required: active/passive/hybrid Intended use: locator, valuator, choice, … Frame of reference: relative vs. absolute Properties sensed: position, motion, force, …

7. (C) 2005 Doug Bowman, Virginia Tech7 Practical classification system Desktop devices Keyboards, 2D mice and trackballs, pen-based tables, joysticks, 6DOF devices for the desktop Tracking devices 3D mice Special-purpose devices Direct human input

8. (C) 2005 Doug Bowman, Virginia Tech8 Desktop devices: keyboards Chord keyboards 1 Arm-mounted keyboards 2 “Soft” keyboards (logical devices)

9. (C) 2005 Doug Bowman, Virginia Tech9 Desktop devices: 6-DOF devices 6 DOFs without tracking Often isometric Exs: Fig. 4.4 SpaceBall 5000, SpaceMouse Plus, SpaceOrb

10. (C) 2005 Doug Bowman, Virginia Tech10 Tracking Devices Motion tracking Eye tracking Data Gloves

11. (C) 2005 Doug Bowman, Virginia Tech11 Tracking devices: position trackers Measure position and/or orientation of a sensor Degrees of freedom (DOFs) Most VEs track the head motion parallax natural viewing

12. (C) 2005 Doug Bowman, Virginia Tech12 Other uses for trackers Track hands, feet, etc. “whole body” interaction motion capture application Correspondence between physical / virtual objects Props 5,6 spatial input devices

13. (C) 2005 Doug Bowman, Virginia Tech13 Tracking physical objects (props)

14. (C) 2005 Doug Bowman, Virginia Tech14 Motion Tracking Critical characteristics Range, latency, jitter (noise or instability), and accuracy Different motion trackers Magnetic Mechanical Acoustic Inertial Optical Hybrid

15. (C) 2005 Doug Bowman, Virginia Tech15 Electromagnetic trackers Exs: Polhemus Fastrak, Ascension Flock of Birds Most common Used with conventional monitors (for fishtank VR) Small workbench displays Transmitter Receiver(s) Noisy Affected by metal objects -> distort the magnetic field

16. (C) 2005 Doug Bowman, Virginia Tech16 Inertial trackers Inertial measurement devices : angular gyroscopes & linear accelerometer Exs: Intersense IS-300, Intertrax2 Less noise, lag Only 3 DOFs (orientation)

17. (C) 2005 Doug Bowman, Virginia Tech17 Optical/vision-based trackers Reflected or emitted light Exs: Vicon, HiBall, ARToolkit Advantages accurate can capture a large volume allow for untethered tracking Disadvantages may require light emitting diodes(LEDs) image processing techniques occlusion problem

18. (C) 2005 Doug Bowman, Virginia Tech18 Optical/vision-based trackers Outside-in or inside-out system Sensors/landmarks – tracked objects/environment Setting up vision-based tracking system can be difficult

19. (C) 2005 Doug Bowman, Virginia Tech19 Hybrid tracking Ex: IS-600 / 900 inertial (orient.) acoustic (pos.) additional complexity, cost

20. (C) 2005 Doug Bowman, Virginia Tech20 Tracking devices: eye tracking

21. (C) 2005 Doug Bowman, Virginia Tech21 Tracking devices: eye tracking User controlling a mouse pointer strictly with his eyes. Gazed direction based - Head-tracker as an approximation to where the user is looking. Problem can occur. - Improve these gaze-directed techniques

22. (C) 2005 Doug Bowman, Virginia Tech22 Tracking devices: bend-sensing gloves CyberGlove 7, 5DT Reports hand posture Gesture: single posture series of postures posture(s) + location or motion

23. (C) 2005 Doug Bowman, Virginia Tech23 Tracking devices: pinch gloves Conductive cloth at fingertips Any gesture of 2 to 10 fingers, plus combinations of gestures > 115,000 gestures

24. (C) 2005 Doug Bowman, Virginia Tech24 Case study: Pinch Gloves Pinch gloves are designed to be a combination device (add a position tracker) Very little has been done with Pinch Gloves in VEs - usually 1 or 2 gestures for: Object selection Tool selection Travel

25. (C) 2005 Doug Bowman, Virginia Tech25 Characteristics of Pinch Gloves Relatively low cost Very light User’s hand becomes the device User’s hand posture can change Allow two-handed interaction Huge number of possible gestures

26. (C) 2005 Doug Bowman, Virginia Tech26 Characteristics of Pinch Gloves II Much more reliable than data gloves Support eyes-off input Can diminish “Heisenberg effect” Support context-sensitive gesture interpretation

27. (C) 2005 Doug Bowman, Virginia Tech27 Pinch Gloves in SmartScene 13 Lots of two-handed gestures Scale world Rotate world Travel by “grabbing the air” Menu selection

28. (C) 2005 Doug Bowman, Virginia Tech28 Pinch Gloves for menus TULIP system 14 ND hand selects menu, D hand selects item within menu Limited to comfortable gestures Visual feedback on virtual hands

29. (C) 2005 Doug Bowman, Virginia Tech29 Pinch Gloves for text input Pinch Keyboard 14 Emulate QWERTY Pinch finger to thumb to type letter under that finger Move/rotate hands to change active letters Visual feedback

30. (C) 2005 Doug Bowman, Virginia Tech30 Combining Bend-Sensing Data and Pinch Input Both the Pinch Gloves and bend-sensing gloves have limitations The Flex and Pinch input system is an example of an input device that combines the functionality of the Pinch Gloves system with the bend-sensing technology of a data glove Figure 4.15