Constructing streak surfaces for 3D unsteady vector fields

Visualization of 3D, unsteady flow (4D) is very difficult due to both perceptual challenges and the large size of 4D vector field data. One approach to this challenge is to use integral surfaces to visualize the 4D properties of the field. However the construction of streak surfaces has remained elusive due to problems stemming from expensive computation and complex meshing schemes. We present a novel streak surface construction algorithm that generates the surface using a quadrangular mesh. In contrast to previous approaches the algorithm offers a combination of speed for exploration of 3D unsteady flow, high precision, and places less restriction on data or mesh size due to its CPU-based implementation compared to a GPU-based method. The algorithm can be applied to large data sets because it is based on local operations performed on the quad primitives. We demonstrate the technique on a variety of 3D, unsteady simulation data sets to show its speed and robustness. We also present both a detailed implementation and a performance evaluation. We show that a technique based on quad meshes handles large data sets and can achieve interactive frame rates

Surface-based flow visualization

This is the author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/computers-and-graphics/.With increasing computing power, it is possible to process more complex fluid simulations. However, a gap between increasing\ud data size and our ability to visualize them still remains. Despite the great amount of progress that has been made in the field of\ud flow visualization over the last two decades, a number of challenges remain. Whilst the visualization of 2D flow has many good\ud solutions, the visualization of 3D flow still poses many problems. Challenges such as domain coverage, speed of computation, and\ud perception remain key directions for further research. Flow visualization with a focus on surface-based techniques forms the basis\ud of this literature survey, including surface construction techniques and visualization methods applied to surfaces. We detail our\ud investigation into these algorithms with discussions of their applicability and their relative strengths and drawbacks. We review the\ud most important challenges when considering such visualizations. The result is an up-to-date overview of the current state-of-the-art\ud that highlights both solved and unsolved problems in this rapidly evolving branch of research

09251 Abstracts Collection -- Scientific Visualization

From 06-14-2009 to 06-19-2009, the Dagstuhl Seminar 09251 ``Scientific Visualization \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, over 50 international participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general

Real-time Realistic Rain Rendering

Artistic outdoor filming and rendering need to choose specific weather conditions in order to properly trigger the audience reaction; for instance, rain, one of the most common conditions, is usually employed to transmit a sense of unrest. Synthetic methods to recreate weather are an important avenue to simplify and cheapen filming, but simulations are a challenging problem due to the variety of different phenomena that need to be computed. Rain alone involves raindrops, splashes on the ground, fog, clouds, lightnings, etc. We propose a new rain rendering algorithm that uses and extends present state of the art approaches in this field. The scope of our method is to achieve real-time renders of rain streaks and splashes on the ground, while considering complex illumination effects and allowing an artistic direction for the drops placement. Our algorithm takes as input an artist-defined rain distribution and density, and then creates particles in the scene following these indications. No restrictions are imposed on the dimensions of the rain area, thus direct rendering approaches could rapidly overwhelm current computational capabilities with huge particle amounts. To solve this situation, we propose techniques that, in rendering time, adaptively sample the particles generated in order to only select the ones in the regions that really need to be simulated and rendered. Particle simulation is executed entirely in the graphics hardware. The algorithm proceeds by placing the particles in their updated coordinates. It then checks whether a particle is falling as a rain streak, it has reached the ground and it is a splash or, finally, if it should be discarded because it has entered a solid object of the scene. Different rendering techniques are used for each case. Complex illumination parameters are computed for rain streaks to select textures matching them. These textures are generated in a preprocess step and realistically simulate light when interacting with the optical properties of the water drops

The State of the Art in Flow Visualization: Dense and Texture-Based Techniques

Flow visualization has been a very attractive component of scientific visualization research for a long time. Usually very large multivariate datasets require processing. These datasets often consist of a large number of sample locations and several time steps. The steadily increasing performance of computers has recently become a driving factor for a reemergence in flow visualization research, especially in texture-based techniques. In this paper, dense, texture-based flow visualization techniques are discussed. This class of techniques attempts to provide a complete, dense representation of the flow field with high spatio-temporal coherency. An attempt of categorizing closely related solutions is incorporated and presented. Fundamentals are shortly addressed as well as advantages and disadvantages of the methods. Categories and Subject Descriptors (according to ACM CCS): I.3 [Computer Graphics]: visualization, flow visualization, computational flow visualizatio