Abstract
Modern time-varying flow visualization techniques that rely on advection are able to convey fluid transport, but cannot provide an accurate insight into local flow behavior over time or locally corresponding patterns in unsteady vector fields. We overcome these limitations of purely Lagrangian approaches by generalizing the concept of function fields to time-varying flows. This representation of unsteady vector-fields as stationary function fields, where every position in space is a vector-valued function supports the application of novel analysis techniques based on function correlation, and allows to answer data analysis questions that remain unanswered with classic time-varying vector field analysis techniques. Our results demonstrate how analysis of time-varying flow fields can benefit from a conversion into function field representations and show the robustness of our presented clustering techniques.
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Obermaier, H., Joy, K.I. (2012). Function Field Analysis for the Visualization of Flow Similarity in Time-Varying Vector Fields. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33191-6_25
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DOI: https://doi.org/10.1007/978-3-642-33191-6_25
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