There are no files associated with this item.
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.citation.endPage | 31 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 15 | - |
dc.citation.title | INTERNARIONAL JOURNAL OF FUZZY SYSTEM APPLICATIONS | - |
dc.citation.volume | 1 | - |
dc.contributor.author | Jeon, Moon-Jin | - |
dc.contributor.author | Lee, Sang Wan | - |
dc.contributor.author | Bien, Zeungnam | - |
dc.date.accessioned | 2023-12-22T06:37:51Z | - |
dc.date.available | 2023-12-22T06:37:51Z | - |
dc.date.created | 2019-10-24 | - |
dc.date.issued | 2011 | - |
dc.description.abstract | As an emerging human-computer interaction (HCI) technology, recognition of human hand gesture is considered a very powerful means for human intention reading. To construct a system with a reliable and robust hand gesture recognition algorithm, it is necessary to resolve several major difficulties of hand gesture recognition, such as inter-person variation, intra-person variation, and false positive error caused by meaningless hand gestures. This paper proposes a learning algorithm and also a classification technique, based on multivariate fuzzy decision tree (MFDT). Efficient control of a fuzzified decision boundary in the MFDT leads to reduction of intra-person variation, while proper selection of a user dependent (UD) recognition model contributes to minimization of inter-person variation. The proposed method is tested first by using two benchmark data sets in UCI Machine Learning Repository and then by a hand gesture data set obtained from 10 people for 15 days. The experimental results show a discernibly enhanced classification performance as well as user adaptation capability of the proposed algorithm. | - |
dc.identifier.bibliographicCitation | INTERNARIONAL JOURNAL OF FUZZY SYSTEM APPLICATIONS, v.1, no.3, pp.15 - 31 | - |
dc.identifier.doi | 10.4018/ijfsa.2011070102 | - |
dc.identifier.issn | 2156-177X | - |
dc.identifier.scopusid | 2-s2.0-84897479961 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/28983 | - |
dc.identifier.url | https://www.igi-global.com/gateway/article/55994 | - |
dc.language | 영어 | - |
dc.publisher | IGI Global | - |
dc.title | Hand gesture recognition using multivariate fuzzy decision tree and user adaptation | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | Hand Gesture Recognition | - |
dc.subject.keywordAuthor | Learning Algorithm | - |
dc.subject.keywordAuthor | Model Selection | - |
dc.subject.keywordAuthor | Multivariate Fuzzy Decision Tree | - |
dc.subject.keywordAuthor | User Adaptation | - |
Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Tel : 052-217-1404 / Email : scholarworks@unist.ac.kr
Copyright (c) 2023 by UNIST LIBRARY. All rights reserved.
ScholarWorks@UNIST was established as an OAK Project for the National Library of Korea.