Skip to main navigation Skip to search Skip to main content

User-Dependent Sign Language Recognition Using Motion Detection

  • American University of Sharjah

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

20 Scopus citations

Abstract

Sign language is the primary means of communication used by deaf people. Statistics show that around 360 million people around the world suffer from hearing loss. For those people, communication with hearing people is a tiring day to day process which may have an adverse effect on their lives. Sign Language Recognition (SLR) is relatively new area, it is not as mature as speech recognition for example. Moreover, Arabic Sign Language Recognition (ArSLR) did not receive much of attention until recent years. This paper presents a continuous sensor-based ArSLR system based on Hidden Markov Models(HMM) and a modified version of k-nearest neighbor(KNN). The proposed system is tested on two datasets. The first was collected using DG5-VHand data gloves and the second was collected using Polhemus G4 tracker. Each dataset was collected by a different signer. Both datasets consist of 40 Arabic sentences with 80-word perplexity. It is intended to make the collected datasets available for the research community. The proposed system provides an excellent performance of 97% sentence recognition rate.

Original languageEnglish
Title of host publicationProceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016
EditorsMary Yang, Hamid R. Arabnia, Leonidas Deligiannidis, Leonidas Deligiannidis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages852-856
Number of pages5
ISBN (Electronic)9781509055104
DOIs
StatePublished - 17 Mar 2017
Externally publishedYes
Event2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016 - Las Vegas, United States
Duration: 15 Dec 201617 Dec 2016

Publication series

NameProceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016

Conference

Conference2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016
Country/TerritoryUnited States
CityLas Vegas
Period15/12/1617/12/16

Keywords

  • Arabic Sign Language Recognition
  • HMM
  • Modefied KNN
  • Motion detector

Fingerprint

Dive into the research topics of 'User-Dependent Sign Language Recognition Using Motion Detection'. Together they form a unique fingerprint.

Cite this