Share Email Print

Proceedings Paper

Viewing angle uncertainty in volumetric visualization
Author(s): Abigail Joseph; Suresh Kumar Lodha; Tao Starbow
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Many direct volume rendering algorithms are routinely used to render volumetric data in scientific applications. Different algorithms, however, produce different results and may lead to different interpretations of the scientific data. There are many factors that contribute to different results including the rendering algorithm such as the ray tracing or projection method. Within the algorithm itself such as ray tracing, there are many factors such as the number of samples, desired opacity, sample location etc., that lead to different images. In some of these cases, the differences between the images are significant enough to demand further investigation. In this work we investigate the sensitivity of differences between images to the viewing angle. In other words, we employ different visualization methods and obtain different images for the same viewing angle. The dependence of these differences on the viewing angle is then investigated. These difference images are visualized by pasting them on six sides of a cube corresponding to six different viewing angles. These differences are also visualized by using glyphs on a sphere, where each point on a sphere corresponds to a viewing angle. For most viewing angles, these differences are not significant and therefore, in such cases, inexpensive visualization algorithms can be employed. In some cases, where the differences are large, our technique compels the user to incorporate uncertainty while drawing conclusions from those images. We also discuss extensions of this work to incorporate uncertainty in volumetric visualization corresponding to different choices of color mapping or opacity.

Paper Details

Date Published: 14 May 1998
PDF: 11 pages
Proc. SPIE 3298, Visual Data Exploration and Analysis V, (14 May 1998); doi: 10.1117/12.309532
Show Author Affiliations
Abigail Joseph, Univ. of California/Santa Cruz (United States)
Suresh Kumar Lodha, Univ. of California/Santa Cruz (United States)
Tao Starbow, Univ. of California/Santa Cruz (United States)

Published in SPIE Proceedings Vol. 3298:
Visual Data Exploration and Analysis V
Robert F. Erbacher; Alex Pang, Editor(s)

© SPIE. Terms of Use
Back to Top