Real-time sign language recognition with guided deep convolutional neural networks

Zhengzhe Liu, Fuyang Huang, Gladys Wai Lan Tang, Felix Yim Binh Sze, Jing Qin, Xiaogang Wang, Qiang Xu

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

7 Citations (Scopus)


We develop a real-time, robust and accurate sign language recognition system leveraging deep convolutional neural networks(DCNN). Our framework is able to prevent common problems such as error accumulation of existing frameworks and it outperforms state-of-the-art frameworks in terms of accuracy, recognition time and usability.
Original languageEnglish
Title of host publicationSUI 2016 - Proceedings of the 2016 Symposium on Spatial User Interaction
PublisherAssociation for Computing Machinery, Inc
Number of pages1
ISBN (Electronic)9781450340687
Publication statusPublished - 15 Oct 2016
Externally publishedYes
Event4th Symposium on Spatial User Interaction, SUI 2016 - Tokyo, Japan
Duration: 15 Oct 201616 Oct 2016


Conference4th Symposium on Spatial User Interaction, SUI 2016


  • Convolutional neural networks
  • Sign language recognition

ASJC Scopus subject areas

  • Human-Computer Interaction

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