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Toward Automatic Sign Language Recognition from Web3D Based Scenes

  • Kabil Jaballah
  • Mohamed Jemni
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6180)

Abstract

This paper describes the development of a 3D continuous sign language recognition system. Since many systems like WebSign[1], Vsigns[2] and eSign[3] are using Web3D standards to generate 3D signing avatars, 3D signed sentences are becoming common. Hidden Markov Models is the most used method to recognize sign language from video-based scenes, but in our case, since we are dealing with well formatted 3D scenes based on H-anim and X3D standards, Hidden Markov Models (HMM) is a too costly double stochastic process. We present a novel approach for sign language recognition using Longest Common Subsequence method. Our recognition experiments were based on a 500 signs lexicon and reach 99 % of accuracy.

Keywords

Sign Language X3D/VRML Gesture recognition Web3D scenes H-Anim Virtual reality 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Kabil Jaballah
    • 1
  • Mohamed Jemni
    • 1
  1. 1.UTIC Research LaboratoryHigh School Of Science and Techniques of TunisBab MnaraTunisia

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