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dc.contributor.authorJang, I. Y.-
dc.contributor.authorLim, H. S.-
dc.contributor.authorAn, S. C.-
dc.date.accessioned2024-01-19T21:02:15Z-
dc.date.available2024-01-19T21:02:15Z-
dc.date.created2021-09-02-
dc.date.issued2019-01-10-
dc.identifier.issn0013-5194-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/120471-
dc.description.abstractA method which simply generates evaluation data for scene flow testing is presented, in which most algorithms for scene flow estimation require a pair of depth and colour images. We scanned the 3D geometry of a real object and rendered it in graphical space to acquire its depth and colour information. Next, surface deformation to generate natural motion for the scene flow is employed. The surface deformation enabled the generation of non-rigid as well as rigid motion. Next, barycentric coefficients were exploited to compute the ground truth scene flow. The coefficients enabled the acquired dense scene to flow accurately without dense point tracking and colour information. On the other hand, each flow vector was computed per pixel and a pixel could come from more than one point due to occlusion. We compute the flow maps dividing the geometry into the front area and the occluded area by modifying a z-buffer algorithm. Experimental results showed that the proposed method reliably provided evaluation data (a pair of depth and colour images and a scene flow map) based on a scanned model with occlusion.-
dc.languageEnglish-
dc.publisherINST ENGINEERING TECHNOLOGY-IET-
dc.titleSimple method for generating evaluation data for scene flow algorithms-
dc.typeArticle-
dc.identifier.doi10.1049/el.2018.6856-
dc.description.journalClass1-
dc.identifier.bibliographicCitationELECTRONICS LETTERS, v.55, no.1, pp.24 - 25-
dc.citation.titleELECTRONICS LETTERS-
dc.citation.volume55-
dc.citation.number1-
dc.citation.startPage24-
dc.citation.endPage25-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000455018800012-
dc.identifier.scopusid2-s2.0-85059679723-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalResearchAreaEngineering-
dc.type.docTypeArticle-
dc.subject.keywordAuthorimage colour analysis-
dc.subject.keywordAuthormotion estimation-
dc.subject.keywordAuthorrendering (computer graphics)-
dc.subject.keywordAuthorcomputational geometry-
dc.subject.keywordAuthorimage resolution-
dc.subject.keywordAuthorscene flow algorithms-
dc.subject.keywordAuthorscene flow testing-
dc.subject.keywordAuthorscene flow estimation-
dc.subject.keywordAuthorcolour images-
dc.subject.keywordAuthorgraphical space-
dc.subject.keywordAuthorcolour information-
dc.subject.keywordAuthorsurface deformation-
dc.subject.keywordAuthorbarycentric coefficients-
dc.subject.keywordAuthorground truth scene flow-
dc.subject.keywordAuthorflow vector-
dc.subject.keywordAuthorflow maps-
dc.subject.keywordAuthorz-buffer algorithm-
dc.subject.keywordAuthorscene flow map-
dc.subject.keywordAuthordepth images-
dc.subject.keywordAuthordense scene-
dc.subject.keywordAuthorevaluation data generation-
dc.subject.keywordAuthor3D geometry-
dc.subject.keywordAuthornatural motion generation-
dc.subject.keywordAuthorrigid motion generation-
dc.subject.keywordAuthornonrigid motion generation-
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KIST Article > 2019
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