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Tablet-Based Gaze Tracker P13541

By: Matt Kelly (CE), Michael Krenzer (EE), Hemsley Pichardo (EE), Tina Podrasky (ISE), Brad Wideman (CE). Tablet-Based Gaze Tracker P13541. Agenda. Project Description Project Goal Customer Needs Project Specifications Final Design Bill of Material Design Summary

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Tablet-Based Gaze Tracker P13541

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  1. By: Matt Kelly (CE), Michael Krenzer (EE), HemsleyPichardo (EE), Tina Podrasky (ISE), Brad Wideman(CE) Tablet-Based Gaze Tracker P13541

  2. Agenda • Project Description • Project Goal • Customer Needs • Project Specifications • Final Design • Bill of Material • Design Summary • System Testing Results • Current State of Project • Conclusion/ Results • Suggestions for Future Work

  3. Project Description • Gaze-Tracking used as a teaching tool for photography • Allows for the greatest level of mobility • Design a portable gaze-tracker that used two cameras simultaneously • One facing the user • One facing the area of interest

  4. Customer Needs

  5. Project Specifications

  6. Final Design

  7. Bill Of Material

  8. Design Summary

  9. Mount Design Summary • Mount Design • Used ABS Plastic for Casing • Used Aluminum for mount • Used GoPro parts for clip

  10. PCB Design Summary • Designed with PCB Express • Two Boards used with 3 LEDs each • Powered off USB • 1.1”x 1.6” each

  11. IR Testing

  12. Focus Testing

  13. Camera Testing

  14. Accuracy Test

  15. Usability Testing • 15 SUBJECTS RUN FOUR RANDOMIZED CALIBRATION ROUTINE • THE SUBJECT FOLLOW A SINGLE DOT TO FIVE DIFFERENT LOCATIONS ON THE SCREEN • TWO DIFFERENT CALIBRATION VARIABLES - FAST OR SLOW AND WITH OR WITHOUT DIRECTION • FAST WITH DIRECTION WAS DETERMINED TO BE THE MOST ACCURATE ROUTINE

  16. Current State of Project • Hardware completed • Camera filter removed and reassembled • IR LEDs and PCBs integrated • Case and Mount manufactured and assembled • Software completed • User Interface • Calibration • Debug Image • Gaze Tracking (with poor accuracy) • Software in Progress • Gaze Tracking Reliability • Pupil Detection • Eye Region Detection • Overall Program Reliability

  17. Conclusions/ Results • Many Customer needs were met, but gaze tracking should be more robust • We learned a lot • Gaze tracking is a very tough problem, especially on a tablet • Learned importance of communication

  18. Suggestions for Future Work • Further work on making our system more accurate and dynamic • Screen to adjust algorithm parameters • Open source, portable library for gaze tracking • Use more Computer Engineers for future iterations

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