GuideME: Slice-guided Semiautomatic Multivariate Exploration of Volumes

dc.contributor.authorZhou, Liangen_US
dc.contributor.authorHansen, Charlesen_US
dc.contributor.editorH. Carr, P. Rheingans, and H. Schumannen_US
dc.date.accessioned2015-03-03T12:34:37Z
dc.date.available2015-03-03T12:34:37Z
dc.date.issued2014en_US
dc.description.abstractMultivariate volume visualization is important for many applications including petroleum exploration and medicine. State-of-the-art tools allow users to interactively explore volumes with multiple linked parameter-space views. However, interactions in the parameter space using trial-and-error may be unintuitive and time consuming. Furthermore, switching between different views may be distracting. In this paper, we propose GuideME: a novel slice-guided semiautomatic multivariate volume exploration approach. Specifically, the approach comprises four stages: attribute inspection, guided uncertainty-aware lasso creation, automated feature extraction and optional spatial fine tuning and visualization. Throughout the exploration process, the user does not need to interact with the parameter views at all and examples of complex real-world data demonstrate the usefulness, efficiency and ease-of-use of our method.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.identifier.doi10.1111/cgf.12371en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12371en_US
dc.publisherThe Eurographics Association and John Wiley and Sons Ltd.en_US
dc.titleGuideME: Slice-guided Semiautomatic Multivariate Exploration of Volumesen_US
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