Optical flow rendering

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dc.contributor.authorPark, TJko
dc.contributor.authorLee, Sko
dc.contributor.authorShin, Sung-Yongko
dc.date.accessioned2013-02-27T14:26:36Z-
dc.date.available2013-02-27T14:26:36Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued1998-
dc.identifier.citationCOMPUTER GRAPHICS FORUM, v.17, no.3, pp.75 - 75-
dc.identifier.issn0167-7055-
dc.identifier.urihttp://hdl.handle.net/10203/69075-
dc.description.abstractThis paper proposes a new approach to image-based rendering that generates an image viewed from an arbitrary camera position and orientation by rendering optical flows extracted from reference images. To derive valid optical flows, we develop an analysis technique that improves the quality of stereo matching. Without using any special equipments such as range cameras, this technique constructs reliable optical flows from a sequence of matching results between reference images. We also derive validity conditions of optical flows and show that the obtained flows satisfy those conditions. Since environment geometry is inferred from the optical flows, we are able to generate more accurate images with this additional geometric information. Our approach makes it possible to combine an image rendered from optical flows with an image generated by a conventional rendering technique through a simple Z-buffer algorithm.-
dc.languageEnglish-
dc.publisherBLACKWELL PUBL LTD-
dc.titleOptical flow rendering-
dc.typeArticle-
dc.identifier.wosid000077820200012-
dc.identifier.scopusid2-s2.0-0003193103-
dc.type.rimsART-
dc.citation.volume17-
dc.citation.issue3-
dc.citation.beginningpage75-
dc.citation.endingpage75-
dc.citation.publicationnameCOMPUTER GRAPHICS FORUM-
dc.contributor.localauthorShin, Sung-Yong-
dc.contributor.nonIdAuthorPark, TJ-
dc.contributor.nonIdAuthorLee, S-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorimage-based rendering-
dc.subject.keywordAuthoroptical flow-
dc.subject.keywordAuthorstereo matching-
dc.subject.keywordAuthordepth information-
dc.subject.keywordAuthorwarp function-
dc.subject.keywordAuthorstatistical analysis-
dc.subject.keywordAuthorimage composition-
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