A virtual keyboard implementation based on finger recognition

@article{Zhang2017AVK,
  title={A virtual keyboard implementation based on finger recognition},
  author={Yongtang Zhang and W. Yan and Ajit Narayanan},
  journal={2017 International Conference on Image and Vision Computing New Zealand (IVCNZ)},
  year={2017},
  pages={1-6}
}
Keyboards still remain as the most popular input medium of choice for users needing to input large amounts of error-free text or combinations of text and numeric data. As mobile devices are being designed smaller, it becomes increasingly difficult for users to enter large amounts of input without carrying and attaching a keyboard. In this paper, we develop a new type of virtual keyboard that allows users to type on any plane to any device. The virtual keyboard is customized and printed on plain… CONTINUE READING

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Key Quantitative Results

  • The experiment results indicate that the overall recognition rate of the proposed virtual keyboard is 94.62%.
  • The results generated from these sessions demonstrated a recognition accuracy of 98.0% and proved that the neural network could be effectively used for a virtual reality driving training system.
  • Under extensive testing, the proposed system was found to be a success in regards to hand gesture recognition due to its promising recognition success rate of 90.45%.
  • Experiments demonstrated that the system was capable of identifying seven common hand gestures and was effective in 34 controlling household appliances with accuracy rates ranging from 82.7% to 97.2%.

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