research-article

Enhancing hand gesture recognition using fuzzy clustering-based mixture-of-experts model

Authors:

Sung-Bae ChoAuthors Info & Claims

ICUIMC '11: Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication

Article No.: 72, Pages 1 - 7

https://doi.org/10.1145/1968613.1968700

Published: 21 February 2011 Publication History

Abstract

Hand gestures have been widely applied to interface as the way of interaction between human and computers. Since a human hand can express various shapes of gestures, previous models for recognizing them cannot distinguish them accurately since they use only single model for recognition. For efficient hand gesture recognition with its enhanced performance, we propose the fuzzy c-means clustering based mixture-of-experts (FME). The proposed method uses multiple local experts obtained via fuzzy c-means clustering and decisions from them are combined with the gating network. To evaluate the performance of the proposed method, we conduct experiments including comparisons with alternative models for hand gesture recognition. As the result of experiments, the proposed model shows improved gesture recognition performance, especially performance on similar hand gesture recognition.

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Cited By

Ghosh ASaha SGhosh L(2023)A rehabilitation framework based on motor imagery induced wheelchair movement using fuzzy vector quantizationInternational Journal of Information Technology10.1007/s41870-023-01359-815:6(3025-3036)Online publication date: 15-Jul-2023
https://doi.org/10.1007/s41870-023-01359-8
He ZLi XZhang ZZhang YXiao JZhou X(2016)Structure-Aware Slow Feature Analysis for Age EstimationIEEE Signal Processing Letters10.1109/LSP.2016.260253823:12(1702-1706)Online publication date: Dec-2016
https://doi.org/10.1109/LSP.2016.2602538
Gaus YWong FTeo KChin RPorle RLim Pei Yi Chekima A(2013)Comparison study of Hidden Markov Model gesture recognition using fixed state and variable state2013 IEEE International Conference on Signal and Image Processing Applications10.1109/ICSIPA.2013.6707994(150-155)Online publication date: Oct-2013
https://doi.org/10.1109/ICSIPA.2013.6707994
Show More Cited By

Index Terms

Enhancing hand gesture recognition using fuzzy clustering-based mixture-of-experts model
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Supervised learning by classification
    2. Machine learning approaches
      1. Classification and regression trees

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Published In

cover image ACM Conferences

ICUIMC '11: Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication

February 2011

959 pages

ISBN:9781450305716

DOI:10.1145/1968613

General Chairs:
Suk-Han Lee
Sungkyunkwan University, Korea
,
Lajos Hanzo
University of Southampton
,
Program Chairs:
Min Young Chung
Sungkyunkwan University, Korea
,
Sang-Won Lee
Sungkyunkwan University, Korea
,
Kwangsu Cho
University of Missouri

Copyright © 2011 ACM.

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SIGAPP: ACM Special Interest Group on Applied Computing
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
SKKU: SUNGKYUNKWAN UNIVERSITY

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 February 2011

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ICUIMC '11: The 5th International Conference on Ubiquitous Information Management and Communication

February 21 - 23, 2011

Seoul, Korea

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ICUIMC '11 Paper Acceptance Rate 135 of 534 submissions, 25%;

Overall Acceptance Rate 251 of 941 submissions, 27%

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Cited By

Ghosh ASaha SGhosh L(2023)A rehabilitation framework based on motor imagery induced wheelchair movement using fuzzy vector quantizationInternational Journal of Information Technology10.1007/s41870-023-01359-815:6(3025-3036)Online publication date: 15-Jul-2023
https://doi.org/10.1007/s41870-023-01359-8
He ZLi XZhang ZZhang YXiao JZhou X(2016)Structure-Aware Slow Feature Analysis for Age EstimationIEEE Signal Processing Letters10.1109/LSP.2016.260253823:12(1702-1706)Online publication date: Dec-2016
https://doi.org/10.1109/LSP.2016.2602538
Gaus YWong FTeo KChin RPorle RLim Pei Yi Chekima A(2013)Comparison study of Hidden Markov Model gesture recognition using fixed state and variable state2013 IEEE International Conference on Signal and Image Processing Applications10.1109/ICSIPA.2013.6707994(150-155)Online publication date: Oct-2013
https://doi.org/10.1109/ICSIPA.2013.6707994
Lekova ADimitrova M(2013)Hand gestures recognition based on lightweight evolving fuzzy clustering method2013 IEEE Second International Conference on Image Information Processing (ICIIP-2013)10.1109/ICIIP.2013.6707644(505-510)Online publication date: Dec-2013
https://doi.org/10.1109/ICIIP.2013.6707644

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