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ASLLENGE

ASLLENGE. He Zhou Hui Zheng William Mai Xiang Guo Advisor: Professor Patrick Kelly. Outline. Background System Requirements Design Challenges System Overview Hardware and Software Team Roles Timeline Q/A. 2. Background.

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ASLLENGE

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  1. ASLLENGE He Zhou HuiZheng William Mai Xiang Guo Advisor: Professor Patrick Kelly

  2. Outline • Background • System Requirements • Design Challenges • System Overview • Hardware and Software • Team Roles • Timeline • Q/A 2

  3. Background • Leverage Kinect technology to recognize and offer feedback on American Sign Language • ASL is the one of most commonly used language in US(.5 to 2 million population use ASL as their primary form of communication) • Educational learning tool for ASL 3

  4. Motivation • Helping hearing impaired people to learn ASL. • Facilitate communication between ASL speaker and non-speaker 4

  5. System Requirements • Create a user-friendly interface that recognize sign language and offer feedback • Software must be easy to use • Display translated word or phase being demonstrated by user • Provide quality feedback to user concerning the accuracy of ASL • Cost should be within the budget 5

  6. Design Challenges • Human Factors • Background Interferences • Finger Gestures • Hardware limitation • Kinect only has 320x240 resolution and 16 bit depth 6

  7. Kinect • Has a depth and regular Camera • Associated with software development kit • Able to track a human being. • Use computer generated algorithms to form human skeleton data points • Track upper body movements 7

  8. System Overview 8

  9. Video demonstration(Hand Rotation) 9

  10. Video demonstration(Hand Crossing) 10

  11. Video demonstration(Hand behind Head) 11

  12. Video demonstration(Hand behind Back) 12

  13. Hardware Implementation 1 • Increasing the flex sensor output voltage with bend • Voltage output goes into an AD converter board • AD converter digitizes the output signal • PC captures the signal via USB or Bluetooth 13

  14. Hardware Implementation 2 • Kinect Camera captures the raw image and the depth image data • The data send to PC to be processed into skeleton tracker • Combining the signal from flex sensor and search in database for matching motions 14

  15. Software Design Flow 15

  16. Development Model 16

  17. Cost of Major Components 17

  18. Team Roles • He - test and integrate software prototype • Hui- image processing and programming • William - build microcontroller to detect finger and palm movements • Xiang- website, overall testing and building ASL database 18

  19. MDR deliverables The goal for our MDR is to be able to detect and track arm and hand positions, possibly be able to translate simple hand gestures 19

  20. Conclusion Our project is good for SDP: • Contains both hardware and software • Expandable: database, audio recognition, braile Our project is a good product: • Aid the disabled people • Personal/commercial use • Relatively inexpensive 20

  21. Timeline 21

  22. Q&A 22

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