Institute for Data Analysis and Visualization

This paper presents a study of field line visualization techniques. To address both the computational and perceptual issues in visualizing large scale, complex, dense field line data commonly found in many scientific applications, a new texture-based field line representation which we call selforienting surfaces is introduced. This scalable representation facilitates hardware-accelerated rendering and incorporation of various perceptually-effective techniques, resulting in intuitive visualization and interpretation of the data under study. An electromagnetic data set obtained from accelerator modeling and a fluid flow data set from aerodynamics modeling are used for evaluation and demonstration of the techniques.