1. WiDraw: Enabling Hands- free Drawing in the Air on Commodity WiFi Devices

2. Outline  Introduction  System  Challenges and Solutions  Evaluation  Conclusion

3. Introduction  There are many ways to do hand motion tracking  Is there a way to track the hand motion that is much simpler ?

4. Outline  Introduction  System  Challenges and Solutions  Evaluation  Conclusion

5. Motion Tracking Ideas  Use existed applications to do hand writing recognition  Use existed work to do 1D AoA recognition

6. System Architecture

7. Hardware  prototype on HP Envy laptops, using Atheros AR9590 chipsets and 3 antennas

8. Outline  Introduction  System  Challenges and Solutions  Evaluation  Conclusion

9. Calculate the AoA

10. Calculate the AoA (2)

11. Discover and Calculate New AoA  There might be new AoA for the system to track  The new AoA can be calculated by the coordinate of the hands.  The system needs at least two spots to calculate a spot passed by the signal beam.  Using the equations below to calculate the azimuth and elevation to calculate the AoA

12. AoA requirements  The signal strength for specific AoA couldn’t change rapidly, ex moving cell-phone, Wi-Fi AP with strength changing periodicity.  How to remove it  Using previous work  Bringing Mobility-Awareness to WLANs using PHY Layer Information

13. Tracking the Hand’s Coordinate -- Tracking the Hand’s Depth Depth – the distance from hand to the line of Antenna array

14. What if depth change We need to know the initial depth and the time which has maximum drop at each AoA - t0, t1, t2 a = (t1-t0)/(t2-t0)

15. The Hand Coordinate  We could calculate the distance between the hand and the trajectory of the incoming signal  Using RSSI can help us know if the hand is moving away from an incoming signal or toward the incoming signal  Use the above observation to calculate the hand position

16. An Example to track hand position

17. Dealing with Environmental Issues

18.  Another way is to ignore the change if the duration between the last change is too long.  T is 1.5 sec, this may lower the accuracy and yield a false positive rate less than 0.04 events/minute

19. Outline  Introduction  System  Challenges and Solutions  Evaluation  Conclusion

20. Evaluation – 2D Drawing Evaluation

21. Evaluation – 3D Drawing Evaluation

22. Evaluation – Real Environment

23. Letter Recognition  Success recognition rate for individual letter.  Left number for upper-case, Right number for lowwer-case  Using the writing reorganization application - MyScript Stylus

24. Letter Recognition  Horizontal Distance: Distance from hand position to the line orthogonal with antenna arrays.

25. Letter Recognition  Width: the letter’s width

26. Letter Recognition

27. Word Recognition According to letter reorganization result, the horizontal range is 100cm and letter width 30cm => write at most three letters at a time

28. Word Recognition  Accuracy rate against word length

29. Word Recognition  Accuracy Rate against different users

30. Outline  Introduction  System  Challenges and Solutions  Evaluation  Conclusion

31. Conclusion

32. Limitation  Wi-Draw using multiple antennas to track hand’s position, but most laptop has only one or two antennas.  Need robust AoA strength for tracking positions