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DC poleHodnotaJazyk
dc.contributor.authorOhnishi, Youhei
dc.contributor.authorNozaki, Kazunori
dc.contributor.authorBaba, Ken-ichi
dc.contributor.editorSkala, Václav
dc.date.accessioned2013-02-07T11:23:22Z-
dc.date.available2013-02-07T11:23:22Z-
dc.date.issued2010
dc.identifier.citationWSCG ’2010: Poster Proceedings: 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in co-operation with EUROGRAPHICS, p. 49-52.en
dc.identifier.isbn978-80-86943-86-2
dc.identifier.urihttp://wscg.zcu.cz/WSCG2010/Papers_2010/!_2010_Poster-proceedings.pdf
dc.identifier.urihttp://hdl.handle.net/11025/1113
dc.description.abstractIn this paper, we propose the segmentation technique by using Snakes for 4dimentional magnetic resonance imaging (MRI) data of the movements of the oral tract shapes when pronunciation is performed. In the segmentation of the time-sequence MRI images, there is the specific problem that depends on a tongue shape quick deformation. We found that the Optical Flow of image sets is useful criteria for the decision of the geometry of control points in Snakes. Compared to the normal Snakes, our original method which modified Snakes by utilizing Optical Flow demonstrated superior accuracy of the segmentation of 4D MRI data.en
dc.format4 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.relation.ispartofseriesWSCG ’2010: Poster Proceedingsen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectsegmentacecs
dc.subjectaktivní konturycs
dc.subject4D zobrazovánícs
dc.subjectoptický tokcs
dc.subjectmagnetická rezonancecs
dc.titleSegmentation technique based on object movement for Speech Production simulationen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatedsegmentationen
dc.subject.translatedactive contoursen
dc.subject.translated4D imagingen
dc.subject.translatedoptical flowen
dc.subject.translatedmagnetic resonanceen
dc.type.statusPeer-revieweden
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