• DocumentCode
    564880
  • Title

    3D Arabic sign language recognition using linear combination of multiple 2D views

  • Author

    Tolba, M.F ; Samir, Ahmed ; Abul-Ela, Magdy

  • Author_Institution
    Scientific Computing Department, Faculty of Computer and information Sciences, Ain Shams University; Cairo, Egypt
  • fYear
    2012
  • fDate
    14-16 May 2012
  • Abstract
    Earlier researchers in sign language recognition faced a problem in some signs because of the single view based recognition. A model is proposed and developed for multiple-views hand postures recognition. Pulse Coupled Neural Network is used to generate features vector for single view. Two views with different view angles are used; each view generates its features vector. The two 2D-vectors then are linearly combined with weights to produce 3D features which will be used in recognition
  • Keywords
    IEEE Xplore; Portable document format; 3D object recognition; Arabic Sign Language (ASL); Puke Coupled Neural Network (PCNN); dynamic gesture; static posture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Informatics and Systems (INFOS), 2012 8th International Conference on
  • Conference_Location
    Cairo
  • Print_ISBN
    978-1-4673-0828-1
  • Type

    conf

  • Filename
    6236611
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=564880