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dc.contributor.authorEdmunds, Matten_US
dc.contributor.authorLaramee, Robert S.en_US
dc.contributor.authorMalki, Ramien_US
dc.contributor.authorMasters, Ianen_US
dc.contributor.authorCroft, Nicken_US
dc.contributor.authorChen, Guoningen_US
dc.contributor.authorZhang, Eugeneen_US
dc.contributor.editorS. Bruckner, S. Miksch, and H. Pfisteren_US
dc.date.accessioned2015-02-28T07:02:21Z
dc.date.available2015-02-28T07:02:21Z
dc.date.issued2012en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttp://dx.doi.org/10.1111/j.1467-8659.2012.03102.xen_US
dc.description.abstractThe ability to capture and visualize information within the flow poses challenges for visualizing 3D flow fields. Stream surfaces are one of many useful integration based techniques for visualizing 3D flow. However seeding integral surfaces can be challenging. Previous research generally focuses on manual placement of stream surfaces. Little attention has been given to the problem of automatic stream surface seeding. This paper introduces a novel automatic stream surface seeding strategy based on vector field clustering. It is important that the user can define and target particular characteristics of the flow. Our framework provides this ability. The user is able to specify different vector clustering parameters enabling a range of abstraction for the density and placement of seeding curves and their associated stream surfaces. We demonstrate the effectiveness of this automatic stream surface approach on a range of flow simulations and incorporate illustrative visualization techniques. Domain expert evaluation of the results provides valuable insight into the users requirements and effectiveness of our approach.en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleAutomatic Stream Surface Seeding: A Feature Centered Approachen_US
dc.description.seriesinformationComputer Graphics Forumen_US


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