Sign language recognition

Recognizing the needs of the hearing impaired community, a new software application was developed to minimize the communication barrier between the deaf people and the general public. With the use of Kinect camera and C++ programming language, a Sign Language program was created. This program is...

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Main Author: Goh, Jia Hui
Other Authors: School of Electrical and Electronic Engineering
Format: Final Year Project
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/10356/61446
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-614462019-12-10T14:02:35Z Sign language recognition Goh, Jia Hui School of Electrical and Electronic Engineering Yuan Junsong DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Recognizing the needs of the hearing impaired community, a new software application was developed to minimize the communication barrier between the deaf people and the general public. With the use of Kinect camera and C++ programming language, a Sign Language program was created. This program is able to interpret the user’s gestures and display the corresponding words on the screen. Thus this amazing program would not only benefit the hearing impaired, but also serves as an interactive and interesting learning tool for those who are willing to learn Sign Language skill. The Sign Language program has high commercial value with great potential for further development in the next few years. Even though there are several different Sign Languages available, but the most prevalent is the American Sign Language (ASL) to cater to the deaf people. In time to come, the Sign Language program will become a useful tool which not only aids to minimize the communication barrier between the deaf people and the general public, but also serves as a learning apparatus which inspires the general public to take up Sign Language skill in the future. Bachelor of Engineering 2014-06-10T06:20:19Z 2014-06-10T06:20:19Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/61446 en Nanyang Technological University 38 p. application/msword
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Goh, Jia Hui
Sign language recognition
description Recognizing the needs of the hearing impaired community, a new software application was developed to minimize the communication barrier between the deaf people and the general public. With the use of Kinect camera and C++ programming language, a Sign Language program was created. This program is able to interpret the user’s gestures and display the corresponding words on the screen. Thus this amazing program would not only benefit the hearing impaired, but also serves as an interactive and interesting learning tool for those who are willing to learn Sign Language skill. The Sign Language program has high commercial value with great potential for further development in the next few years. Even though there are several different Sign Languages available, but the most prevalent is the American Sign Language (ASL) to cater to the deaf people. In time to come, the Sign Language program will become a useful tool which not only aids to minimize the communication barrier between the deaf people and the general public, but also serves as a learning apparatus which inspires the general public to take up Sign Language skill in the future.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Goh, Jia Hui
format Final Year Project
author Goh, Jia Hui
author_sort Goh, Jia Hui
title Sign language recognition
title_short Sign language recognition
title_full Sign language recognition
title_fullStr Sign language recognition
title_full_unstemmed Sign language recognition
title_sort sign language recognition
publishDate 2014
url http://hdl.handle.net/10356/61446
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