DC Field | Value | Language |
---|---|---|
dc.contributor.author | 장태영 | - |
dc.contributor.author | 강성현 | - |
dc.contributor.author | 박현우 | - |
dc.contributor.author | 김성대 | - |
dc.date.accessioned | 2016-07-07T05:09:57Z | - |
dc.date.available | 2016-07-07T05:09:57Z | - |
dc.date.created | 2016-06-26 | - |
dc.date.issued | 2016-06-24 | - |
dc.identifier.citation | 2016년도 대한전자공학회 하계학술대회 | - |
dc.identifier.uri | http://hdl.handle.net/10203/209767 | - |
dc.description.abstract | Hand shape classification is an important problem for the human computer interaction and the fingerspelling recognition. These problems need a real-time process and scale invariance. To this end, we propose a feature vector for hand shape classification which is fast, and robust to scale. The proposed method calculates an adaptive k-curvature which computes a curvature depending on the hand size. The proposed method works at 0.08sec per image and has a 99% accuracy. | - |
dc.language | Korean | - |
dc.publisher | 대한전자공학회 | - |
dc.title | 스케일에 강인한 곡률 특징 벡터를 활용한 실시간 손 모양 분류 기법 | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 2016년도 대한전자공학회 하계학술대회 | - |
dc.identifier.conferencecountry | KO | - |
dc.identifier.conferencelocation | 대한민국, 제주도 | - |
dc.contributor.localauthor | 장태영 | - |
dc.contributor.localauthor | 강성현 | - |
dc.contributor.localauthor | 박현우 | - |
dc.contributor.localauthor | 김성대 | - |
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