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이희승

Lee, Hui Sung
Design & Electronic Convergence System Lab.
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DC Field Value Language
dc.citation.endPage 873 -
dc.citation.number 5 -
dc.citation.startPage 863 -
dc.citation.title IEEE TRANSACTIONS ON ROBOTICS -
dc.citation.volume 23 -
dc.contributor.author Lee, Hui Sung -
dc.contributor.author Park, Jeong Woo -
dc.contributor.author Chung, Myting Jin -
dc.date.accessioned 2023-12-22T09:09:04Z -
dc.date.available 2023-12-22T09:09:04Z -
dc.date.created 2017-03-29 -
dc.date.issued 2007-10 -
dc.description.abstract A robot's face is its symbolic feature, and its facial expressions are the best method for interacting with people with emotional information. Moreover, a robot's facial expressions play an important role in human-robot emotional interactions. This paper proposes a general rule for the design and realization of expressions when some mascot-type facial robots are developed. Mascot-type facial robots are developed to enable friendly human feelings. The number and type of control points for six basic expressions or emotions were determined through a questionnaire. A linear affect-expression space model is provided to realize continuous and various expressions effectively, and the effects of the proposed method are shown through experiments using a simulator and an actual robot system. -
dc.identifier.bibliographicCitation IEEE TRANSACTIONS ON ROBOTICS, v.23, no.5, pp.863 - 873 -
dc.identifier.doi 10.1109/TRO.2007.907477 -
dc.identifier.issn 1552-3098 -
dc.identifier.scopusid 2-s2.0-35348870442 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/21798 -
dc.identifier.url http://ieeexplore.ieee.org/document/4339538/?reload=true -
dc.identifier.wosid 000250177900004 -
dc.language 영어 -
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC -
dc.title A linear affect-expression space model and control points for mascot-type facial robots -
dc.type Article -
dc.description.isOpenAccess FALSE -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor affect space -
dc.subject.keywordAuthor emotion -
dc.subject.keywordAuthor facial expression -
dc.subject.keywordAuthor facial robot -
dc.subject.keywordPlus EMOTION -

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