DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cho, E | - |
dc.contributor.author | Kim, D | - |
dc.contributor.author | Lee, SY | - |
dc.date.accessioned | 2016-03-31T12:46:34Z | - |
dc.date.available | 2016-03-31T12:46:34Z | - |
dc.date.created | 2009-02-28 | - |
dc.date.issued | 2003-01 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.other | 2003-OAK-0000003630 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/18374 | - |
dc.description.abstract | This paper proposes to synthesize posed facial images from two parameters for the pose. This parameterization makes the representation, storage, and transmission of face images effective. Because variations of face images show a complicated nonlinear manifold in high-dimensional data space, we use an LLE (Locally Linear Embedding) technique for a good representation of face images. And we apply a snake model to estimate face feature values in the reduced feature space that corresponds to a specific pose parameter. Finally, a synthetic face image is obtained from an interpolation of several neighboring face images. Experimental results show that the proposed method creates an accurate and consistent synthetic face images with respect to changes of pose. | - |
dc.description.statementofresponsibility | X | - |
dc.language | English | - |
dc.publisher | SPRINGER-VERLAG BERLIN | - |
dc.relation.isPartOf | LECTURE NOTES IN COMPUTER SCIENCE | - |
dc.subject | DIMENSIONALITY REDUCTION | - |
dc.title | Posed face image synthesis using nonlinear manifold learning | - |
dc.type | Article | - |
dc.contributor.college | 컴퓨터공학과 | - |
dc.identifier.doi | 10.1007/3-540-44887-x_110 | - |
dc.author.google | Cho, E | - |
dc.author.google | Kim, D | - |
dc.author.google | Lee, SY | - |
dc.relation.volume | 2688 | - |
dc.relation.startpage | 946 | - |
dc.relation.lastpage | 954 | - |
dc.contributor.id | 10054411 | - |
dc.relation.journal | LECTURE NOTES IN COMPUTER SCIENCE | - |
dc.relation.index | SCI급, SCOPUS 등재논문 | - |
dc.relation.sci | SCIE | - |
dc.collections.name | Conference Papers | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | LECTURE NOTES IN COMPUTER SCIENCE, v.2688, pp.946 - 954 | - |
dc.identifier.wosid | 000184940200110 | - |
dc.date.tcdate | 2019-01-01 | - |
dc.citation.endPage | 954 | - |
dc.citation.startPage | 946 | - |
dc.citation.title | LECTURE NOTES IN COMPUTER SCIENCE | - |
dc.citation.volume | 2688 | - |
dc.contributor.affiliatedAuthor | Kim, D | - |
dc.identifier.scopusid | 2-s2.0-33745620410 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.wostc | 2 | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Imaging Science & Photographic Technology | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Imaging Science & Photographic Technology | - |
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