Data visualization using automatic perceptually motivated shapes
Chris Shaw, David S. Ebert, James M. Kukla, Amen Zwa, Ian M. Soboroff, D. A. Roberts · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
This paper describes a new technique for the multi-dimensional visualization of data through automatic procedural generation of glyph shapes based on mathematical functions. Our glyph- based Stereoscopic Field Analyzer (SFA) system allows the visualization of both regular and irregular grids of volumetric data. SFA uses a glyph's location, 3D size, color and opacity to encode up to 8 attributes of scalar data per glyph. We have extended SFA's capabilities to explore shape variation as a visualization attribute. We opted for a procedural approach, which allows flexibility, data abstraction, and freedom from specification of detailed shapes. Superquadrics are a natural choice to satisfy our goal of automatic and comprehensible mapping of data to shape. For our initial implementation we have chosen superellipses. We parameterize superquadrics to allow continuous control over the 'roundness' or 'pointiness' of the shape in the two major planes which intersect to form the shape, allowing a very simple, intuitive, abstract schema of shape specification.