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Seipp, Karsten; Devlin, Kate (2015)
Publisher: ACM
Languages: English
Types: Unknown

Classified by OpenAIRE into

We present a technique that allows distinguishing between index finger and thumb input on touchscreen phones, achieving an average accuracy of 82.6% in a real-life application with only a single touch. We divide the screen into a virtual grid of 9mmx9mm units and use a dedicated set of training data and algorithms for classifying new touches in each screen location. Further, we present correlations between physical and digital touch properties to extend previous work.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • 11. Wang, F., Cao, X., Ren, X., and Irani, P. Detecting and leveraging finger orientation for interaction with direct-touch surfaces. In Proc.UIST'09, 23-32.
    • 12. Wang, F., and Ren, X. Empirical evaluation for finger input properties in multi-touch interaction. In Proc.CHI'09, 1063-1072.
    • 13. Wilson, G., Brewster, S. A., Halvey, M., Crossan, A., and Stewart, C. The effects of walking, feedback and control method on pressure-based interaction. In Proc.MHCI'11, 147-156.
    • 14. Wimmer, R., and Boring, S. HandSense: discriminating different ways of grasping and holding a tangible user interface. In Proc.TEI'09, 359-362.
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