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Depth estimation from stereo cameras through a curved transparent medium

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dc.contributor.authorYoon, Seongwook-
dc.contributor.authorChoi, Taehyeon-
dc.contributor.authorSull, Sanghoon-
dc.date.accessioned2021-08-31T14:50:41Z-
dc.date.available2021-08-31T14:50:41Z-
dc.date.created2021-06-19-
dc.date.issued2020-01-
dc.identifier.issn0167-8655-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/58407-
dc.description.abstractIn this paper, we propose a novel method for estimating depth values by stereo cameras through a curved transparent medium that causes refraction. Our method takes both the surface shape of the medium and the refraction into account. We model that the rays from the stereo cameras are refracted by a curved transparent medium whose inner surface is represented by a parametric model, assuming that the medium has constant thickness. The parameters of the model are estimated using a constrained optimization simply by attaching several markers on the inner surface. The depth value is then estimated by the triangulation considering the refraction based on the model. The experimental results show that our method yields consistently high error reduction rates with respect to the baseline method without considering the refraction caused by the medium. In addition, our method provides satisfactory estimates for various shapes of the medium. (C) 2019 Elsevier B.V. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER-
dc.subjectRECONSTRUCTION-
dc.titleDepth estimation from stereo cameras through a curved transparent medium-
dc.typeArticle-
dc.contributor.affiliatedAuthorSull, Sanghoon-
dc.identifier.doi10.1016/j.patrec.2019.11.012-
dc.identifier.scopusid2-s2.0-85075218788-
dc.identifier.wosid000504641500015-
dc.identifier.bibliographicCitationPATTERN RECOGNITION LETTERS, v.129, pp.101 - 107-
dc.relation.isPartOfPATTERN RECOGNITION LETTERS-
dc.citation.titlePATTERN RECOGNITION LETTERS-
dc.citation.volume129-
dc.citation.startPage101-
dc.citation.endPage107-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.subject.keywordPlusRECONSTRUCTION-
dc.subject.keywordAuthorDepth from stereo-
dc.subject.keywordAuthorCamera calibration-
dc.subject.keywordAuthorRefraction-
dc.subject.keywordAuthorParametric surface model-
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