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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Selection Classification for Interaction with Immersive Volumetric Visualizations
verfasst von : Amy Banic
Erschienen in: Human Interface and the Management of Information. Information and Knowledge Design and Evaluation
Verlag: Springer International Publishing
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Visualization enables scientists to transform data in its raw form to a visual form that will facilitate discoveries and insights. Although there are advantages for displaying inherently 3-dimensional (3D) data in immersive environments, those advantages are hampered by the challenges involved in selecting volumes of that data for exploration or analysis. Selection involves the user identifying a set of points for a specific task. This paper preliminary data collection on natural user actions for volume selection. This paper also presents a research agenda outlining an extension for volume selection classification, as well as challenges, for designing components for a direct selection of volumes of data points.