DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, JB | ko |
dc.contributor.author | Bien, ZN | ko |
dc.date.accessioned | 2013-03-03T20:20:10Z | - |
dc.date.available | 2013-03-03T20:20:10Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2004-05 | - |
dc.identifier.citation | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E87D, pp.1265 - 1270 | - |
dc.identifier.issn | 0916-8532 | - |
dc.identifier.uri | http://hdl.handle.net/10203/80274 | - |
dc.description.abstract | We present a method for recognition of continuous Korean Sign Language (KSL). In the paper, we consider the segmentation problem of a continuous hand motion pattern in KSL. For this, we first extract sign sentences by removing linking gestures between sign sentences. We use a gesture tension model and fuzzy partitioning. Then, each sign sentence is disassembled into a set of elementary motions (EMs) according to its geometric pattern. The hidden Markov model is adopted to classify the segmented individual EMs. | - |
dc.language | English | - |
dc.publisher | IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG | - |
dc.title | Recognition of continuous Korean sign language using gesture tension model and soft computing technique | - |
dc.type | Article | - |
dc.identifier.wosid | 000221445100027 | - |
dc.identifier.scopusid | 2-s2.0-2642571855 | - |
dc.type.rims | ART | - |
dc.citation.volume | E87D | - |
dc.citation.beginningpage | 1265 | - |
dc.citation.endingpage | 1270 | - |
dc.citation.publicationname | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | - |
dc.contributor.localauthor | Bien, ZN | - |
dc.contributor.nonIdAuthor | Kim, JB | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | sign language recognition | - |
dc.subject.keywordAuthor | gesture recognition | - |
dc.subject.keywordAuthor | continuous gesture | - |
dc.subject.keywordAuthor | gesture tension model | - |
dc.subject.keywordAuthor | soft computing | - |
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