We present a parallel visualization algorithm for the illustrative rendering of depth-dependent stylized dense tube data at interactive frame rates. While this computation could be efficiently performed on a GPU device, we target a parallel framework to enable it to be efficiently running on an ordinary multi-core CPU platform which is much more available than GPUs for common users. Our approach is to map the depth information in each tube onto each of the visual dimensions of shape, color, texture, value, and size on the basis of Bertin's semiology theory. The purpose is to enable more legible displays in the dense tube environments. A major contribution of our work is an efficient and effective parallel depthordering algorithm that makes use of the message passing interface (MPI) with VTK. We evaluated our framework with visualizations of depth-stylized tubes derived from 3D diffusion tensor MRI data by comparing its efficiency with several other alternative parallelization platforms running the same computations. As our results show, the parallelization framework we proposed can efficiently render highly dense 3D data sets like the tube data and thus is useful as a complement to parallel visualization environments that rely on GPUs.
There have been many previous work dedicating to technical solutions to the depth perception issues and visual occlusions in 3D data visualizations. To name a few, a rich set of landmarks and context cues @cite_6 and shading and transparency @cite_8 both contribute in enhancing visual perception in the depth dimension while alleviating occlusion problems within overlapping structures. Focusing on strengthening depth perception, employ volumetric halos to improve the 3D legibility of visualized volume data @cite_1 . They introduce different halos according to different ways of halo-volume combination and use halos to construct inconsistent lighting, which accentuates depth even further from another aspect.
@cite_1 @cite_6 @cite_8
2158707602 2147394532
Volumetric data commonly has high depth complexity which makes it difficult to judge spatial relationships accurately. There are many different ways to enhance depth perception, such as shading, contours, and shadows. Artists and illustrators frequently employ halos for this purpose. In this technique, regions surrounding the edges of certain structures are darkened or brightened which makes it easier to judge occlusion. Based on this concept, we present a flexible method for enhancing and highlighting structures of interest using GPU-based direct volume rendering. Our approach uses an interactively defined halo transfer function to classify structures of interest based on data value, direction, and position. A feature-preserving spreading algorithm is applied to distribute seed values to neighboring locations, generating a controllably smooth field of halo intensities. These halo intensities are then mapped to colors and opacities using a halo profile function. Our method can be used to annotate features at interactive frame rates. Navigating through large-scale virtual environments such as simulations of the astrophysical Universe is difficult. The huge spatial range of astronomical models and the dominance of empty space make it hard for users to travel across cosmological scales effectively, and the problem of wayfinding further impedes the user's ability to acquire reliable spatial knowledge of astronomical contexts. We introduce a new technique called the scalable world-in-miniature (WIM) map as a unifying interface to facilitate travel and wayfinding in a virtual environment spanning gigantic spatial scales: power-law spatial seating enables rapid and accurate transitions among widely separated regions; logarithmically mapped miniature spaces offer a global overview mode when the full context is too large; 3D landmarks represented in the WIM are enhanced by scale, positional, and directional cues to augment spatial context awareness; a series of navigation models are incorporated into the scalable WIM to improve the performance of travel tasks posed by the unique characteristics of virtual cosmic exploration. The scalable WIM user interface supports an improved physical navigation experience and assists pragmatic cognitive understanding of a visualization context that incorporates the features of large-scale astronomy