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Sign Language Recognition Using Leap Motion

A Support Vector Machine Approach
  • Luis QuesadaEmail author
  • Gustavo López
  • Luis A. Guerrero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9454)

Abstract

Several million people around the world use signs as their main mean of communication. The advances in technologies to recognize such signs will make possible the computer supported interpretation of sign languages. There are more than 137 different sign language around the world; therefore, a system that interprets those languages could be beneficial to all, including the Deaf Community. This paper presents a system based on a hand tracking device called Leap Motion, used for signs recognition. The system uses a Support Vector Machine for sign classification. We performed three different evaluations of our system with over 24 people.

Keywords

American Sign Language Leap Motion Support Vector Machine Automatic sign language recognition 

Notes

Acknowledgments

This work was partially supported by the Escuela de Ciencias de la Computación e Informática at Universidad de Costa Rica (ECCI-UCR) grand No. 320-B5-291, by Centro de Investigaciones en Tecnologías de la Información y Comunicación de la Universidad de Costa Rica (CITIC-UCR), and by Ministerio de Ciencia, Tecnología y Telecomunicaciones (MICITT) and Consejo Nacional para Investigaciones Científicas y Tecnológicas (CONICIT) of the Government of Costa Rica.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Luis Quesada
    • 1
    Email author
  • Gustavo López
    • 2
  • Luis A. Guerrero
    • 1
    • 2
  1. 1.Escuela de Ciencias de La Computación E InformáticaUniversidad de Costa RicaSan PedroCosta Rica
  2. 2.Centro de Investigaciones En Tecnologías de La Información Y ComunicaciónUniversidad de Costa RicaSan PedroCosta Rica

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