A Fast hierarchical traversal strategy for multimodal visualization

In the last years there is a growing demand of multimodal medical rendering systems able to visualize simultaneously data coming from different sources. This paper addresses the Direct Volume Rendering (DVR) of aligned multimodal data in medical applications. Specifically, it proposes a hierarchical representation of the multimodal data set based on the construction of a Fusion Decision Tree (FDT) that, together with a run-length encoding of the non-empty data, provides means of efficiently accessing to the data. Three different implementations of these structures are proposed. The simulations results show that the traversal of the data is fast and that the method is suitable when interactive modifications of the fusion parameters are required.Postprint (published version

Assessment of School Effectiveness in Greece using Multilevel Models

In recent years, a lot of attention has been given to the so-called “performance indicators”, which are primarily used for institutional comparisons. Education and health are the area in which these indicators are widely applied, serving the needs of modern societies for highly qualified rendering of servicesMultilevel modeling, Hierarchical data, Performance indicators, School effectiveness

MKtree: generation and simulations

The problem to represent very complex systems has been studied by several authors, obtaining solutions based on different data structures. In this paper, a K dimensional tree (Multirresolution Kdtree, MKtree) is introduced. The MKtree represents a hierarchical subdivision of the scene objects that guarantees a minimum space overlap between node regions. MKtrees are useful for collision detection and for time-critical rendering in very large environments requiring external memory storage. Examples in ship design applications are described.Postprint (published version

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

Synthesis of Multiresolution Scenes with Global Illumination on a GPU

[Abstract] The radiosity computation has the important feature of producing view independent results, but these results are mesh dependent and, in consequence, are attached to a specific level of detail in the input mesh. Therefore, rendering at iterative frame rates would benefit from the utilization of multiresolution models. In this paper we focus on the rendering stage of a solution for hierarchical radiosity for multiresolution systems. This method is based on the application of an enriched hierarchical radiosity algorithm to an input scene with low resolution objects (represented by coarse meshes), and the efficient data management of the resulting values. The proposed encoding makes it possible to apply the color values obtained for the coarse objects to detailed versions of these objects during the rendering phase. These finer meshes are obtained by a standard mesh subdivision strategy, such as the Loop subdivision scheme. Our solution performs the whole rendering stage of this multiresolution approach on the GPU, implementing it in the geometry shader using Microsoft HLSL. Results of our implementation show an important reduction in computational costs

An efficient multi-resolution framework for high quality interactive rendering of massive point clouds using multi-way kd-trees

We present an efficient technique for out-of-core multi-resolution construction and high quality interactive visualization of massive point clouds. Our approach introduces a novel hierarchical level of detail (LOD) organization based on multi-way kd-trees, which simplifies memory management and allows control over the LOD-tree height. The LOD tree, constructed bottom up using a fast high-quality point simplification method, is fully balanced and contains all uniformly sized nodes. To this end, we introduce and analyze three efficient point simplification approaches that yield a desired number of high-quality output points. For constant rendering performance, we propose an efficient rendering-on-a-budget method with asynchronous data loading, which delivers fully continuous high quality rendering through LOD geo-morphing and deferred blending. Our algorithm is incorporated in a full end-to-end rendering system, which supports both local rendering and cluster-parallel distributed rendering. The method is evaluated on complex models made of hundreds of millions of point sample

Time-Critical Volume Rendering

For the past twelve months, we have conducted and completed a joint research entitled "Time- Critical Volume Rendering" with NASA Ames. As expected, High performance volume rendering algorithms have been developed by exploring some new faster rendering techniques, including object presence acceleration, parallel processing, and hierarchical level-of-detail representation. Using our new techniques, initial experiments have achieved real-time rendering rates of more than 10 frames per second of various 3D data sets with highest resolution. A couple of joint papers and technique reports as well as an interactive real-time demo have been compiled as the result of this project

Incremental volume rendering using hierarchical compression

Includes bibliographical references.The research has been based on the thesis that efficient volume rendering of datasets, contained on the Internet, can be achieved on average personal workstations. We present a new algorithm here for efficient incremental rendering of volumetric datasets. The primary goal of this algorithm is to give average workstations the ability to efficiently render volume data received over relatively low bandwidth network links in such a way that rapid user feedback is maintained. Common limitations of workstation rendering of volume data include: large memory overheads, the requirement of expensive rendering hardware, and high speed processing ability. The rendering algorithm presented here overcomes these problems by making use of the efficient Shear-Warp Factorisation method which does not require specialised graphics hardware. However the original Shear-Warp algorithm suffers from a high memory overhead and does not provide for incremental rendering which is required should rapid user feedback be maintained. Our algorithm represents the volumetric data using a hierarchical data structure which provides for the incremental classification and rendering of volume data. This exploits the multiscale nature of the octree data structure. The algorithm reduces the memory footprint of the original Shear-Warp Factorisation algorithm by a factor of more than two, while maintaining good rendering performance. These factors make our octree algorithm more suitable for implementation on average desktop workstations for the purposes of interactive exploration of volume models over a network. This dissertation covers the theory and practice of developing the octree based Shear-Warp algorithms, and then presents the results of extensive empirical testing. The results, using typical volume datasets, demonstrate the ability of the algorithm to achieve high rendering rates for both incremental rendering and standard rendering while reducing the runtime memory requirements