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

Jong Won Yoon, Jun Ki Min, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011
DOIs
Publication statusPublished - 2011
Event5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011 - Seoul, Korea, Republic of
Duration: 2011 Feb 212011 Feb 23

Publication series

NameProceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011

Other

Other5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011
Country/TerritoryKorea, Republic of
CitySeoul
Period11/2/2111/2/23

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

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