TetSplat: Real-time Rendering and Volume Clipping of Large Unstructured Tetrahedral Meshes

We present a novel approach to interactive visualization and exploration of large unstructured tetrahedral meshes. These massive 3D meshes are used in mission-critical CFD and structural mechanics simulations, and typically sample multiple field values on several millions of unstructured grid points. Our method relies on the pre-processing of the tetrahedral mesh to partition it into non-convex boundaries and internal fragments that are subsequently encoded into compressed multi-resolution data representations. These compact hierarchical data structures are then adaptively rendered and probed in real-time on a commodity PC. Our point-based rendering algorithm, which is inspired by QSplat, employs a simple but highly efficient splatting technique that guarantees interactive frame-rates regardless of the size of the input mesh and the available rendering hardware. It furthermore allows for real-time probing of the volumetric data-set through constructive solid geometry operations as well as interactive editing of color transfer functions for an arbitrary number of field values. Thus, the presented visualization technique allows end-users for the first time to interactively render and explore very large unstructured tetrahedral meshes on relatively inexpensive hardware

Compression domain volume rendering for distributed environments

This paper describes a method for volume data compression and rendering which bases on wavelet splats. The underlying concept is especially designed for distributed and networked applications, where we assume a remote server to maintain large scale volume data sets, being inspected, browsed through and rendered interactively by a local client. Therefore, we encode the server‘s volume data using a newly designed wavelet based volume compression method. A local client can render the volumes immediately from the compression domain by using wavelet footprints, a method proposed earlier. In addition, our setup features full progression, where the rendered image is refined progressively as data comes in. Furthermore, framerate constraints are considered by controlling the quality of the image both locally and globally depending on the current network bandwidth or computational capabilities of the client. As a very important aspect of our setup, the client does not need to provide storage for the volume data and can be implemented in terms of a network application. The underlying framework enables to exploit all advantageous properties of the wavelet transform and forms a basis for both sophisticated lossy compression and rendering. Although coming along with simple illumination and constant exponential decay, the rendering method is especially suited for fast interactive inspection of large data sets and can be supported easily by graphics hardware

Hardware and software improvements of volume splatting

This paper proposes different hardware-based acceleration of the three classical splatting strategies: emph{composite-every-sample}, emph{object-space sheet-buffer} and emph{image-space sheet-buffer}.Preprin

Design of a multimodal rendering system

This paper addresses the rendering of aligned regular multimodal datasets. It presents a general framework of multimodal data fusion that includes several data merging methods. We also analyze the requirements of a rendering system able to provide these different fusion methods. On the basis of these requirements, we propose a novel design for a multimodal rendering system. The design has been implemented and proved showing to be efficient and flexible.Postprint (published version

VolumeEVM: A new surface/volume integrated model

Volume visualization is a very active research area in the field of scien-tific visualization. The Extreme Vertices Model (EVM) has proven to be a complete intermediate model to visualize and manipulate volume data using a surface rendering approach. However, the ability to integrate the advantages of surface rendering approach with the superiority in visual exploration of the volume rendering would actually produce a very complete visualization and edition system for volume data. Therefore, we decided to define an enhanced EVM-based model which incorporates the volumetric information required to achieved a nearly direct volume visualization technique. Thus, VolumeEVM was designed maintaining the same EVM-based data structure plus a sorted list of density values corresponding to the EVM-based VoIs interior voxels. A function which relates interior voxels of the EVM with the set of densities was mandatory to be defined. This report presents the definition of this new surface/volume integrated model based on the well known EVM encoding and propose implementations of the main software-based direct volume rendering techniques through the proposed model.Postprint (published version

14-08 Big Data Analytics to Aid Developing Livable Communities

In transportation, ubiquitous deployment of low-cost sensors combined with powerful computer hardware and high-speed network makes big data available. USDOT defines big data research in transportation as a number of advanced techniques applied to the capture, management and analysis of very large and diverse volumes of data. Data in transportation are usually well organized into tables and are characterized by relatively low dimensionality and yet huge numbers of records. Therefore, big data research in transportation has unique challenges on how to effectively process huge amounts of data records and data streams. The purpose of this study is to conduct research on the problems caused by large data volume and data streams and to develop applications for data analysis in transportation. To process large number of records efficiently, we have proposed to aggregate the data at multiple resolutions and to explore the data at various resolutions to balance between accuracy and speed. Techniques and algorithms in statistical analysis and data visualization have been developed for efficient data analytics using multiresolution data aggregation. Results will be helpful in setting up a primitive stage towards a rigorous framework for general analytical processing of big data in transportation

Time-varying volume visualization

Volume rendering is a very active research field in Computer Graphics because of its wide range of applications in various sciences, from medicine to flow mechanics. In this report, we survey a state-of-the-art on time-varying volume rendering. We state several basic concepts and then we establish several criteria to classify the studied works: IVR versus DVR, 4D versus 3D+time, compression techniques, involved architectures, use of parallelism and image-space versus object-space coherence. We also address other related problems as transfer functions and 2D cross-sections computation of time-varying volume data. All the papers reviewed are classified into several tables based on the mentioned classification and, finally, several conclusions are presented.Preprin