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dc.contributor.authorFrey, Steffenen_US
dc.contributor.editorJeffrey Heer and Heike Leitte and Timo Ropinskien_US
dc.description.abstractWe visualize contours for spatio-temporal processes to indicate where and when non-continuous changes occur or spatial bounds are encountered. All time steps are comprised densely in one visualization, with contours allowing to efficiently analyze processes in the data even in case of spatial or temporal overlap. Contours are determined on the basis of deep raycasting that collects samples across time and depth along each ray. For each sample along a ray, its closest neighbors from adjacent rays are identified, considering time, depth, and value in the process. Large distances are represented as contours in image space, using color to indicate temporal occurrence. This contour representation can easily be combined with volume rendering-based techniques, providing both full spatial detail for individual time steps and an outline of the whole time series in one view. Our view-dependent technique supports efficient progressive computation, and requires no prior assumptions regarding the shape or nature of processes in the data. We discuss and demonstrate the performance and utility of our approach via a variety of data sets, comparison and combination with an alternative technique, and feedback by a domain scientist.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts Human
dc.subjectcentered computing → Visualization techniques
dc.subjectScientific visualization
dc.titleSpatio-Temporal Contours from Deep Volume Raycastingen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersScalar Fields

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  • 37-Issue 3
    EuroVis 2018 - Conference Proceedings

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