dc.citation.conferencePlace |
JA |
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dc.citation.conferencePlace |
Tsukuba; Japan |
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dc.citation.endPage |
286 |
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dc.citation.startPage |
285 |
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dc.citation.title |
2nd International Conference on Human-Agent Interaction, HAI 2014 |
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dc.contributor.author |
Jang, Gil-Jin |
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dc.contributor.author |
Jo, Ahra |
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dc.contributor.author |
Park, Jeong-Sik |
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dc.date.accessioned |
2023-12-20T00:10:56Z |
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dc.date.available |
2023-12-20T00:10:56Z |
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dc.date.created |
2014-12-17 |
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dc.date.issued |
2014 |
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dc.description.abstract |
This abstract introduces an efficient method for identifying various facial expressions from image inputs. To recognize the emotions of the facial expressions, a number of facial feature points were extracted. The extracted feature points are then transformed to 49-dimensional feature vectors which are robust to scale and translational variations, and the facial emotions are recognized by a support vector machine (SVM). Based on the experimental results, SVM performance was obtained by 50.8% for 6 emotion classification, and 78.0% for 3 emotions. |
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dc.identifier.bibliographicCitation |
2nd International Conference on Human-Agent Interaction, HAI 2014, pp.285 - 286 |
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dc.identifier.doi |
10.1145/2658861.2658943 |
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dc.identifier.isbn |
978-145033035-0 |
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dc.identifier.scopusid |
2-s2.0-84914698776 |
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dc.identifier.uri |
https://scholarworks.unist.ac.kr/handle/201301/51332 |
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dc.language |
영어 |
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dc.publisher |
Association for Computing Machinery, Inc |
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dc.title |
Video-based emotion identification using face alignment and support vector machines |
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dc.type |
Conference Paper |
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dc.date.conferenceDate |
2014-10-29 |
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