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Bayesian neural network approach to hand gesture recognition system

  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a hand gesture recognition system as a part of our virtual reality system called non-contact flight auxiliary (NCFAC) system. The system is developed using Bayesian neural network to translate hand gestures to corresponding commands and utilizes one hand gesture to prepare for collision detection. Cyberglove sensory glove and Flock of Birds motion tracker are applied to this system to extract hand features. The Bayesian neural network model is trained and tested with different sample groups. Experiment shows that our system is able to recognize 16 kinds of hand gestures with the accuracy of 95.6% and greater generalization capability. The system can also be extended and use other algorithms for future works.

Original languageEnglish
Title of host publication2014 IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2019-2023
Number of pages5
ISBN (Electronic)9781479946990
DOIs
StatePublished - 12 Jan 2015
Event6th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014 - Yantai, China
Duration: 8 Aug 201410 Aug 2014

Publication series

Name2014 IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014

Conference

Conference6th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014
Country/TerritoryChina
CityYantai
Period8/08/1410/08/14

Keywords

  • Bayesian neural network
  • Gesture recognition
  • Glove
  • Virtual reality

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