VG10: Eurographics/IEEE VGTC on Volume Graphics

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/468

Browse

Browsing VG10: Eurographics/IEEE VGTC on Volume Graphics by Subject "Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Picture/Image Generation-Line and curve generation"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Advanced Light Material Interaction for Direct Volume Rendering
    (The Eurographics Association, 2010) Lindemann, Florian; Ropinski, Timo; Ruediger Westermann and Gordon Kindlmann
    In this paper we present a heuristic approach for simulating advanced light material interactions in the context of interactive volume rendering. In contrast to previous work, we are able to incorporate complex material functions, which allow to simulate reflectance and scattering. We exploit a common representation of these material properties based on spherical harmonic basis functions, to combine the achieved reflectance and scattering effects with natural lighting conditions, i. e., incorporating colored area light sources. To achieve these goals, we introduce a modified SH projection technique, which is not just tailored at a single material category, but adapts to the present material. Thus, reflecting and scattering materials as assigned trough the transfer function can be captured in a unified approach. We will describe the required extensions to the standard volume rendering integral and present an approximation which allows to realize the material effects in order to achieve interactive frame rates. By exploiting a combination of CPU and GPU processing, we are able to modify material properties and can change the illumination conditions interactively. We will demonstrate the outcome of the proposed approach based on renderings of real-world data sets and report the achieved computation times.
  • Thumbnail Image
    Item
    Efficient Acquisition and Clustering of Local Histograms for Representing Voxel Neighborhoods
    (The Eurographics Association, 2010) Meß, Christian; Ropinski, Timo; Ruediger Westermann and Gordon Kindlmann
    In the past years many interactive volume rendering techniques have been proposed, which exploit the neighboring environment of a voxel during rendering. In general on-the-fly acquisition of this environment is infeasible due to the high amount of data to be taken into account. To bypass this problem we propose a GPU preprocessing pipeline which allows to acquire and compress the neighborhood information for each voxel. Therefore, we represent the environment around each voxel by generating a local histogram (LH) of the surrounding voxel densities. By performing a vector quantization (VQ), the high number of LHs is than reduced to a few hundred cluster centroids, which are accessed through an index volume. To accelerate the required computational expensive processing steps, we take advantage of the highly parallel nature of this task and realize it using CUDA. For the LH compression we use an optimized hybrid CPU/GPU implementation of the k-means VQ algorithm. While the assignment of each LH to its nearest centroid is done on the GPU using CUDA, centroid recalculation after each iteration is done on the CPU. Our results demonstrate the applicability of the precomputed data, while the performance is increased by a factor of about 10 compared to previous approaches.
  • Thumbnail Image
    Item
    Multi-dimensional Reduction and Transfer Function Design using Parallel Coordinates
    (The Eurographics Association, 2010) Zhao, Xin; Kaufman, Arie; Ruediger Westermann and Gordon Kindlmann
    Multi-dimensional transfer functions are widely used to provide appropriate data classification for direct volume rendering. Nevertheless, the design of a multi-dimensional transfer function is a complicated task. In this paper, we propose to use parallel coordinates, a powerful tool to visualize high-dimensional geometry and analyze multivariate data, for multi-dimensional transfer function design. This approach has two major advantages: (1) Combining the information of spatial space (voxel position) and parameter space; (2) Selecting appropriate highdimensional parameters to obtain sophisticated data classification. Although parallel coordinates offers simple interface for the user to design the high-dimensional transfer function, some extra work such as sorting the coordinates is inevitable. Therefore, we use a local linear embedding technique for dimension reduction to reduce the burdensome calculations in the high dimensional parameter space and to represent the transfer function concisely. With the aid of parallel coordinates, we propose some novel high-dimensional transfer function widgets for better visualization results. We demonstrate the capability of our parallel coordinates based transfer function (PCbTF) design method for direct volume rendering using CT and MRI datasets.