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dc.contributor.authorKoch, Thomas Bernharden_US
dc.contributor.authorKouril, Daviden_US
dc.contributor.authorKlein, Tobiasen_US
dc.contributor.authorMindek, Peteren_US
dc.contributor.authorViola, Ivanen_US
dc.contributor.editorPuig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pauen_US
dc.date.accessioned2018-09-19T15:20:03Z
dc.date.available2018-09-19T15:20:03Z
dc.date.issued2018
dc.identifier.isbn978-3-03868-056-7
dc.identifier.issn2070-5786
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20181245
dc.identifier.urihttps://doi.org/10.2312/vcbm.20181245
dc.description.abstractVisual clutter is a major problem in large biological data visualization. It is often addressed through the means of level of detail schemes coupled with an appropriate coloring of the visualized structures. Ambient occlusion and shadows are often used to improve the depth perception. However, when used excessively, these techniques are sources of visual clutter themselves. In this paper we present a new approach to screen-space illumination algorithms suitable for use in illustrative visualization. The illumination effect can be controlled so that desired levels of semantic scene organization cast shadows while other remain flat. This way the illumination design can be parameterized to keep visual clutter, originating from illumination, to a minimum, while also guiding the user in a multiscale model exploration. We achieve this by selectively applying occlusion shading based on the inherent semantics of the visualized hierarchically-organized data. The technique is in principle generally applicable to any hierarchically organized 3D scene and has been demonstrated on an exemplary scene from integrative structural biology.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectScientific visualization
dc.titleSemantic Screen-Space Occlusion for Multiscale Molecular Visualizationen_US
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.description.sectionheadersBiology
dc.identifier.doi10.2312/vcbm.20181245
dc.identifier.pages197-201


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