Visualizing Multiple Two-Dimensional Fields of Data in a Single Image

With advancemens in scientific measurement instruments and simulation tech- niques come increasingly complex and in many cases multivariate data. The devel- opment and improvement of techniques that are able to convey as much information as possible from this data to scientists, doctors, and other potential users is an important research topic in the field of scientific visualization. This thesis contributes a new automated approach to the visualization of multiple two-dimensional, spatial data fields in a single image. We introduce a new generative formal grammar called texture grammar that combines implementations of existing visualization techniques and image compositing techniques to automatically produce visualizations, depending on the input fields. The image compositing techniques are perceptually motivated, and we evaluated their effectiveness with a user study. The resulting visualizations capture important characteristics of all input fields, as well as relations between the fields. An added benefit of this method is the reduction of user interaction, since a larger amount of data can be perceived at once.

Subject

data visualization
multi-field visualization
flow visualization
formal grammar
texture grammar

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http://resolver.tudelft.nl/uuid:14523cdc-302e-49c2-bf0f-5062fedecf99

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Student theses

Document type

master thesis

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ccve_thesis_final.pdf

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