Dynamic gesture recognition based on the probabilistic distribution of arm trajectory
Link to publisher's homepage at http://ieeexplore.ieee.org/
Saved in:
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Working Paper |
Language: | English |
Published: |
IEEE Conference Publications
2014
|
Subjects: | |
Online Access: | http://dspace.unimap.edu.my:80/dspace/handle/123456789/34031 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.unimap-34031 |
---|---|
record_format |
dspace |
spelling |
my.unimap-340312014-04-24T04:31:14Z Dynamic gesture recognition based on the probabilistic distribution of arm trajectory Wan Khairunizam, Wan Ahmad, Dr. Sawada, Hideyuki khairunizam@unimap.edu.my Probabilistic distributions Engineering controlled terms Engineering main heading Gesture recognition Fuzzy algorithms Link to publisher's homepage at http://ieeexplore.ieee.org/ The use of human motions for the interaction between humans and computers is becoming an attractive alternative, especially through the visual interpretation of the human body motion. In particular, hand gesture is used as a non-verbal media for the humans to communicate with machines that pertains to the use of human gesture to interact with them. Recently, many studies for recognizing the human gesture have been reported, and most of them deal with the shape and motion of hands. This paper introduces dynamic gesture recognition based on the arm trajectory and fuzzy algorithm approach. In this study, by examining the characteristics of the human upper body motions of a signer, motion features are selected and classified by using the fuzzy technique. Experimental results show that the use of the features extracted from the upper body motion effectively works on the recognition of the dynamic gesture of a human, and gives a good performance to classify various gesture patterns. 2014-04-24T04:31:14Z 2014-04-24T04:31:14Z 2008 Working Paper IEEE International Conference on Mechatronics and Automation, 2008, pages 426-431 978-142442632-4 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4798792&tag=1 http://dspace.unimap.edu.my:80/dspace/handle/123456789/34031 10.1109/ICMA.2008.4798792 en IEEE Conference Publications |
institution |
Universiti Malaysia Perlis |
building |
UniMAP Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Malaysia Perlis |
content_source |
UniMAP Library Digital Repository |
url_provider |
http://dspace.unimap.edu.my/ |
language |
English |
topic |
Probabilistic distributions Engineering controlled terms Engineering main heading Gesture recognition Fuzzy algorithms |
spellingShingle |
Probabilistic distributions Engineering controlled terms Engineering main heading Gesture recognition Fuzzy algorithms Wan Khairunizam, Wan Ahmad, Dr. Sawada, Hideyuki Dynamic gesture recognition based on the probabilistic distribution of arm trajectory |
description |
Link to publisher's homepage at http://ieeexplore.ieee.org/ |
author2 |
khairunizam@unimap.edu.my |
author_facet |
khairunizam@unimap.edu.my Wan Khairunizam, Wan Ahmad, Dr. Sawada, Hideyuki |
format |
Working Paper |
author |
Wan Khairunizam, Wan Ahmad, Dr. Sawada, Hideyuki |
author_sort |
Wan Khairunizam, Wan Ahmad, Dr. |
title |
Dynamic gesture recognition based on the probabilistic distribution of arm trajectory |
title_short |
Dynamic gesture recognition based on the probabilistic distribution of arm trajectory |
title_full |
Dynamic gesture recognition based on the probabilistic distribution of arm trajectory |
title_fullStr |
Dynamic gesture recognition based on the probabilistic distribution of arm trajectory |
title_full_unstemmed |
Dynamic gesture recognition based on the probabilistic distribution of arm trajectory |
title_sort |
dynamic gesture recognition based on the probabilistic distribution of arm trajectory |
publisher |
IEEE Conference Publications |
publishDate |
2014 |
url |
http://dspace.unimap.edu.my:80/dspace/handle/123456789/34031 |
_version_ |
1643797377565327360 |
score |
13.214268 |