Human hand sign language recognition based on extreme learning machine

As machine learning algorithms and computer processing speed greatly advanced in recent years, real-time hand gesture recognition has become a promising topic in computer science and language technology. Some of the existing limits in achieving user-friendly experience are real-time recognition spee...

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Bibliographic Details
Main Author:	Qiao, Cheng
Other Authors:	Huang Guangbin
Format:	Final Year Project
Language:	English
Published:	2015
Subjects:	DRNTU::Engineering::Electrical and electronic engineering
Online Access:	http://hdl.handle.net/10356/64392
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-64392
record_format	dspace
spelling	sg-ntu-dr.10356-643922023-07-07T16:10:18Z Human hand sign language recognition based on extreme learning machine Qiao, Cheng Huang Guangbin School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering As machine learning algorithms and computer processing speed greatly advanced in recent years, real-time hand gesture recognition has become a promising topic in computer science and language technology. Some of the existing limits in achieving user-friendly experience are real-time recognition speed and accuracy. This project aims to realize practical dual hand real-time recognition and to develop new man-machine interaction functions. Based on senior Mr. Jiang Runzhou’s FYP work, Ms. Cai Xiao, Mr. Liu Hongyang and the author work closely to achieve the objective. Realizable functions include PowerPoint slide show control, music player control and Rock, Paper, Scissor game. Mr. Jiang Runzhou’s past gesture recognition is also enhanced to achieve more excellent accuracy. Bachelor of Engineering 2015-05-26T06:30:56Z 2015-05-26T06:30:56Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/64392 en Nanyang Technological University 32 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Electrical and electronic engineering
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering Qiao, Cheng Human hand sign language recognition based on extreme learning machine
description	As machine learning algorithms and computer processing speed greatly advanced in recent years, real-time hand gesture recognition has become a promising topic in computer science and language technology. Some of the existing limits in achieving user-friendly experience are real-time recognition speed and accuracy. This project aims to realize practical dual hand real-time recognition and to develop new man-machine interaction functions. Based on senior Mr. Jiang Runzhou’s FYP work, Ms. Cai Xiao, Mr. Liu Hongyang and the author work closely to achieve the objective. Realizable functions include PowerPoint slide show control, music player control and Rock, Paper, Scissor game. Mr. Jiang Runzhou’s past gesture recognition is also enhanced to achieve more excellent accuracy.
author2	Huang Guangbin
author_facet	Huang Guangbin Qiao, Cheng
format	Final Year Project
author	Qiao, Cheng
author_sort	Qiao, Cheng
title	Human hand sign language recognition based on extreme learning machine
title_short	Human hand sign language recognition based on extreme learning machine
title_full	Human hand sign language recognition based on extreme learning machine
title_fullStr	Human hand sign language recognition based on extreme learning machine
title_full_unstemmed	Human hand sign language recognition based on extreme learning machine
title_sort	human hand sign language recognition based on extreme learning machine
publishDate	2015
url	http://hdl.handle.net/10356/64392
_version_	1772825662888869888

Human hand sign language recognition based on extreme learning machine

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