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Haptics Final Project: Using a Sensor Glove to Write in the Air Paul Taele Spring 2008
Goals <ul><li>Write stuff in the air without a pen. </li></ul>
Initial Gestures
Original Posture Classifier Setup <ul><li>Tools: </li></ul><ul><ul><li>P5 </li></ul></ul><ul><ul><li>CyberGlove </li></ul>...
Postures - Results <ul><li>P5 </li></ul><ul><ul><li>NB: 10% </li></ul></ul><ul><ul><li>kNN: 50% </li></ul></ul><ul><ul><li...
Postures - Analysis <ul><li>Desired 100% for posture classification. </li></ul><ul><li>Used CyberGlove device and Neural N...
Hand Gesture Segmentation <ul><li>Simple for two very separable gestures. </li></ul><ul><li>Classify each time state in an...
Final Project Setup <ul><li>Tools: CyberGlove </li></ul><ul><li>Language: Java </li></ul><ul><li>Posture Classifier: Neura...
Final Postures
Final Gestures
Training Data ($1) <ul><li>Created templates from 3 users. </li></ul><ul><li>Each user gave 5 examples for each sketch ges...
 
 
 
 
Test Data ($1) <ul><li>Data was tested on consecutively-inputted sketch gesture. </li></ul><ul><li>Postures first extracte...
Target: Circle -> Triangle Actual: Rectangle -> Triangle
Target: Rectangle -> Circle Actual: Rectangle -> Rectangle
Target: Triangle -> X Actual: X -> X
Target: X -> Rectangle Actual: Rectangle -> X
Conclusion <ul><li>$1 sucks. </li></ul>
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Haptics Final Project Presentation

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Haptics Final Project Presentation

  1. 1. Haptics Final Project: Using a Sensor Glove to Write in the Air Paul Taele Spring 2008
  2. 2. Goals <ul><li>Write stuff in the air without a pen. </li></ul>
  3. 3. Initial Gestures
  4. 4. Original Posture Classifier Setup <ul><li>Tools: </li></ul><ul><ul><li>P5 </li></ul></ul><ul><ul><li>CyberGlove </li></ul></ul><ul><li>Posture Classifiers: </li></ul><ul><ul><li>k-Nearest Neighbor </li></ul></ul><ul><ul><li>Naïve Bayes </li></ul></ul><ul><ul><li>Neural Network </li></ul></ul>
  5. 5. Postures - Results <ul><li>P5 </li></ul><ul><ul><li>NB: 10% </li></ul></ul><ul><ul><li>kNN: 50% </li></ul></ul><ul><ul><li>NN: 70% </li></ul></ul><ul><li>CyberGlove </li></ul><ul><ul><li>NN: 75% (all 23 sensors) </li></ul></ul><ul><ul><li>NN: 100% (3 index finger sensors) </li></ul></ul>
  6. 6. Postures - Analysis <ul><li>Desired 100% for posture classification. </li></ul><ul><li>Used CyberGlove device and Neural Network classifier for postures. </li></ul><ul><li>Used two easily separable gestures instead of four. </li></ul>
  7. 7. Hand Gesture Segmentation <ul><li>Simple for two very separable gestures. </li></ul><ul><li>Classify each time state in an instance using the trained NN. </li></ul>
  8. 8. Final Project Setup <ul><li>Tools: CyberGlove </li></ul><ul><li>Language: Java </li></ul><ul><li>Posture Classifier: Neural Network </li></ul><ul><li>Sketch Classifier: $1 </li></ul><ul><li># of Postures: 2 </li></ul><ul><li># of Gestures: 4 </li></ul>
  9. 9. Final Postures
  10. 10. Final Gestures
  11. 11. Training Data ($1) <ul><li>Created templates from 3 users. </li></ul><ul><li>Each user gave 5 examples for each sketch gesture. </li></ul>
  12. 16. Test Data ($1) <ul><li>Data was tested on consecutively-inputted sketch gesture. </li></ul><ul><li>Postures first extracted from gesturing stream. </li></ul><ul><li>Time points of those postures used to classify sketch gestures. </li></ul>
  13. 17. Target: Circle -> Triangle Actual: Rectangle -> Triangle
  14. 18. Target: Rectangle -> Circle Actual: Rectangle -> Rectangle
  15. 19. Target: Triangle -> X Actual: X -> X
  16. 20. Target: X -> Rectangle Actual: Rectangle -> X
  17. 21. Conclusion <ul><li>$1 sucks. </li></ul>

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