Abstract
Visualization of multi-dimensional data is a challenging task. The goal is not the display of multiple data dimensions, but user comprehension of the multi-dimensional data. This paper explores several techniques for perceptually motivated procedural generation of shapes to increase the comprehension of multi-dimensional data. Our glyph-based system allows the visualization of both regular and irregular grids of volumetric data. A glyph’s location, 3D size, color, and opacity encode up to 8 attributes of scalar data per glyph. We have extended the system’s capabilities to explore shape variation as a visualization attribute. We use procedural shape generation techniques because they allow flexibility, data abstraction, and freedom from specification of detailed shapes. We have explored three procedural shape generation techniques: fractal detail generation, superquadrics, and implicit surfaces. These techniques allow from 1 to 14 additional data dimensions to be visualized using glyph shape.
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Ebert, D.S., Rohrer, R.M., Shaw, C.D., Panda, P., Kukla, J.M., Roberts, D.A. (1999). Procedural Shape Generation for Multi-dimensional Data Visualization. In: Gröller, E., Löffelmann, H., Ribarsky, W. (eds) Data Visualization ’99. Eurographics. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6803-5_1
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DOI: https://doi.org/10.1007/978-3-7091-6803-5_1
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83344-5
Online ISBN: 978-3-7091-6803-5
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