An improved computer interface comprising a recurrent neural network and a natural user interface

Jiachen Yang, Ryota Horie

Research output: Contribution to journalConference articlepeer-review

8 Citations (Scopus)

Abstract

We developed an interface system by which a user can operate a computer with hand and finger movements. To implement the interface, we used a gesture sensor to acquire the movement-based data. A recurrent neural network (RNN) was included to discriminate types of gestures. Using the proposed interface, high recognition rates were obtained for simple gestures, while the recognition rates of complicated gestures were low. To improve the rate of accuracy in recognizing complicated gestures, we investigated the dependency of factors on the rate of recognition in the RNN learning process and identified settings to refine these factors.

Original languageEnglish
Pages (from-to)1386-1395
Number of pages10
JournalProcedia Computer Science
Volume60
Issue number1
DOIs
Publication statusPublished - 2015
Event19th International Conference on Knowledge Based and Intelligent Information and Engineering Systems, KES 2015 - , Singapore
Duration: 2015 Sep 72015 Sep 9

Keywords

  • Back propagation through time
  • Computer interface
  • Leap motion
  • Natural user interface
  • Recurrent neural network

ASJC Scopus subject areas

  • Computer Science(all)

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