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dc.contributor.authorRosenthal, Paul
dc.contributor.authorMolchanov, Vladimir
dc.contributor.authorLinsen, Lars
dc.contributor.editorSkala, Václav
dc.date.accessioned2014-03-25T08:46:26Z
dc.date.available2014-03-25T08:46:26Z
dc.date.issued2010
dc.identifier.citationWSCG 2010: Full Papers Proceedings: 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in co-operation with EUROGRAPHICS, p. 73-80.en
dc.identifier.isbn978-80-86943-88-6
dc.identifier.urihttp://wscg.zcu.cz/WSCG2010/Papers_2010/!_2010_FULL-proceedings.pdf
dc.identifier.urihttp://hdl.handle.net/11025/10869
dc.description.abstractLevel-set methods have become a valuable and well-established field of visualization over the last decades. Different implementations addressing different design goals and different data types exist. In particular, level sets can be used to extract isosurfaces from scalar volume data that fulfill certain smoothness criteria. Recently, such an approach has been generalized to operate on unstructured point-based volume data, where data points are not arranged on a regular grid nor are they connected in form of a mesh. Utilizing this new development, one can avoid an interpolation to a regular grid which inevitably introduces interpolation errors. However, the global processing of the level-set function can be slow when dealing with unstructured point-based volume data sets containing several million data points. We propose an improved level-set approach that performs the process of the level-set function locally. As for isosurface extraction we are only interested in the zero level set, values are only updated in regions close to the zero level set. In each iteration of the level-set process, the zero level set is extracted using direct isosurface extraction from unstructured point-based volume data and a narrow band around the zero level set is constructed. The band consists of two parts: an inner and an outer band. The inner band contains all data points within a small area around the zero level set. These points are updated when executing the level set step. The outer band encloses the inner band providing all those neighbors of the points of the inner band that are necessary to approximate gradients and mean curvature. Neighborhood information is obtained using an efficient kd-tree scheme, gradients and mean curvature are estimated using a four-dimensional least-squares fitting approach. Comparing ourselves to the global approach, we demonstrate that this local level-set approach for unstructured point-based volume data achieves a significant speed-up of one order of magnitude for data sets in the range of several million data points with equivalent quality and robustness.en
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesWSCG 2010: Full Papers Proceedingsen
dc.rights© Václav Skala - UNION Agencyen
dc.subjectúrovňová sadacs
dc.subjectna bodech založená objemová datacs
dc.subjectextrakce izoplochcs
dc.titleA Narrow Band Level Set Method for Surface Extractionen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatedlevel seten
dc.subject.translatedpoint-based volume dataen
dc.subject.translatedisosurface extractionen
dc.type.statusPeer-revieweden
dc.type.driverinfo:eu-repo/semantics/conferenceObjecten
dc.type.driverinfo:eu-repo/semantics/publishedVersionen
Appears in Collections:WSCG 2010: Full Papers Proceedings

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