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Finger detection evaluation system

Finger detection evaluation system. Su-ting, Chuang. Outline. Introduction Related work Hardware configuration Finger Detection system Optimal parameter estimation framework Conclusion. Outline. Introduction Related work Hardware configuration Finger Detection system

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Finger detection evaluation system

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  1. Finger detection evaluation system Su-ting, Chuang

  2. Outline • Introduction • Related work • Hardware configuration • Finger Detection system • Optimal parameter estimation framework • Conclusion

  3. Outline • Introduction • Related work • Hardware configuration • Finger Detection system • Optimal parameter estimation framework • Conclusion

  4. Introduction • Motivation • Evaluate components in finger detection systems • Verify and improve performance of finger detection systems • Method • Develop an optimal parameter estimation framework • Use most prevalent finger detection system as testbed • Touchlib

  5. Outline • Introduction • Related work • Hardware configuration • Finger Detection system • Optimal parameter estimation framework • Conclusion

  6. Related Work • FTIR (Frustrated Total Internal Reflection) J. Y. Han, “Low-cost multi-touch sensing through frustrated total internal reflection," in Proceedings of the 18th annual ACM symposium on User interface software and technology (UIST '05). New York, NY, USA: ACM Press, 2005, pp. 115-118.

  7. Related Work • DI (Diffused Illumination) J. Rekimoto and N. Matsushita, “Perceptual surfaces: Towards a human and object sensitive interactive display," Workshop on Perceptural User Interfaces (PUI'97), 1997.

  8. Related Work • TouchLib • A multi-touch development kit • Finger detection processing flow chart Mono Background Subtraction Simple Highpass Scale Threshold

  9. Outline • Introduction • Related work • Hardware configuration • Finger Detection system • Optimal parameter estimation framework • Conclusion

  10. Hardware configuration • Table setup

  11. Hardware configuration • Order of diffuser layer and touch-glass layer spot IRcamera IRcamera Diffuser layer Touch-glass layer spot IR illuminator IR illuminator IRcamera IRcamera

  12. Hardware configuration • Problem: • IR rays will be reflected by the touch-glass and resulting hot spot regions in camera views • Solution: • Use other cameras to recover the regions which are sheltered by IR spots

  13. Outline • Introduction • Related work • Hardware configuration • Finger Detection system • Optimal parameter estimation framework • Conclusion

  14. Detection system IR cam Pre-processing Image processing IR cam GPU Finger Analyzing Data Association Data Transmission CPU

  15. Detection system • Pre-processing IR Camera Undistortion HomoWarp Image Fusion (Blend) IR camera Undistortion HomoWarp

  16. Pre-processing • Undistortion • Undistort foreground objects • Warp • Unify finger size among different position of table • Image fusion • Mask hot spots and recover them from the other camera image • Finger at border won’t be discard

  17. Pre-processing • Advantage of implementing on GPU • Increase performance • High frame rate • Preserve CPU for application computation • Enable detection system and interactive application on the same computer • Reduce unsynchronized problemamong different computers

  18. Detection system • Image processing Mono Background Subtraction Normalization Simple Highpass Threshold

  19. Image processing • Normalization • Motivation • Eliminate influence due to non-uniform lighting condition • Various finger touch response • Hard to decide a good threshold • Method • Model distribution of IR illumination • Use specific material to simulate foreground • Calculate each pixel’s dynamic range • Stretch dynamic range to 0-255

  20. Finger Analyzing • Connected component • finger size evaluation

  21. Data association • Fingertip matching • Matching fingertips among frames • Using bipartite algorithm • Fingertip tracking • Smooth detected results and fix lost results • Using Kalman filter

  22. Outline • Introduction • Related work • Hardware configuration • Detection system • Optimal parameter estimation framework • Conclusion

  23. Optimal parameters estimation framework • Motivation • Find optimal parameters for finger detection system

  24. Optimal parameters estimation framework • Procedure • Define parameters for finger detection system • Collect samples • Various finger size • Various hand gesture • Search optimal parameters • Verify performance of all possible parameter combinations

  25. Optimal parameters estimation framework • Collect samples • Task • Soft /Hard touch • Vertical/Oblique touch • Various fingers • Sample set • Each task has 2x2x5 samples • Sample collection • Step-by-step instruction • Straightforward UI design timer 5 Finger touch position Instructions….

  26. Optimal parameters estimation framework • Search optimal parameters • Exhaustive search • Test various parameter combination in each set • Step • Each parameter combination • Detect finger touch • Verify detection result • Calculate error rate

  27. Optimal parameters estimation framework frame Detection system Parameter Set Detection Result Sample set Ground Truth Optimal parameter finder Optimal Parameter Set Detection Result Parameter Set Error Rate Ground Truth Next Parameter Set Generator Verify

  28. Outline • Introduction • Related work • Hardware configuration • Detection system • Optimal parameter estimation framework • Conclusion

  29. Thanks for your attention

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