An Incremental Learning Framework for Skeletal-based Hand Gesture Recognition with Leap Motion

Jie Li, Junpei Zhong, Fei Chen, Chenguang Yang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Hand gesture recognition has become the focus of researchers lately because of its manifold applications in various fields. Leap Motion (LM) is a device to obtain useful and accurate information of the hand action, which is suitable for collecting the three-dimensional (3D) human hand gesture. In this paper, a novel framework which consists of an incremental learning (IL) algorithm without deep structure is proposed and applied to hand gestures classification that explicitly aimed to the LM data. The same datasets are used to train the proposed framework and the conventional Long Short Term Memory Recurrent Neural Network (LSTM-RNN). Due to the structural advantage of the proposed model, the recognition performance is improved distinctly in robustness and training time than the LSTM network. Moreover, convincing experiment results are given to illustrate that the solution is more efficient in static gesture classification.

Original languageEnglish
Title of host publication9th IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, CYBER 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages13-18
Number of pages6
ISBN (Electronic)9781728107691
DOIs
Publication statusPublished - Jul 2019
Externally publishedYes
Event9th IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, CYBER 2019 - Suzhou, China
Duration: 29 Jul 20192 Aug 2019

Publication series

Name9th IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, CYBER 2019

Conference

Conference9th IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, CYBER 2019
Country/TerritoryChina
CitySuzhou
Period29/07/192/08/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization

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