Seamless visual abstraction of molecular surfaces

Julius Parulek, Timo Ropinski, Ivan Viola

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Molecular visualization is often challenged with rendering of large sequences of molecular simulations in real time. We introduce a novel approach that enables us to show even large protein complexes over time in real-time. Our method is based on the level-ofdetail concept, where we exploit three different molecular surface models, solvent excluded surface (SES), Gaussian kernels and van der Waals spheres combined in one visualization. We introduce three shading levels that correspond to their geometric counterparts and a method for creating seamless transition between these representations. The SES representation with full shading and added contours stands in focus while on the other side a sphere representation with constant shading and without contours provide the context. Moreover, we introduce a methodology to render the entire molecule directly using the A-buffer technique, which further improves the performance. The rendering performance is evaluated on series of molecules of varying atom counts.

Original languageEnglish (US)
Title of host publicationProceedings - SCCG 2013
Subtitle of host publication29th Spring Conference on Computer Graphics
PublisherAssociation for Computing Machinery
Pages107-114
Number of pages8
ISBN (Print)9781450324809
DOIs
StatePublished - 2013
Externally publishedYes
Event29th Spring Conference on Computer Graphics, SCCG 2013 - Smolenice, Slovakia
Duration: May 1 2013May 3 2013

Publication series

NameProceedings - SCCG 2013: 29th Spring Conference on Computer Graphics

Conference

Conference29th Spring Conference on Computer Graphics, SCCG 2013
Country/TerritorySlovakia
CitySmolenice
Period05/1/1305/3/13

Keywords

  • Implicit surfaces
  • Level-of-detail
  • Visualization of molecular surfaces

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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