Graph and tree visualization techniques enable interactive exploration of complex relations while communicating topology. However, most existing techniques have not been designed for situations where visual informatio...
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Graph and tree visualization techniques enable interactive exploration of complex relations while communicating topology. However, most existing techniques have not been designed for situations where visual information such as images is also present at each node and must be displayed. This paper presents MoireGraphs to address this need. MoireGraphs combine a new focus+context radial graph layout with a suite of interaction techniques (focus strength changing, radial rotation, level highlighting, secondary foci, animated transitions and node information) to assist in the exploration of graphs with visual nodes. The method is scalable to hundreds of displayed visual nodes.
We present a robust image synthesis method to automatically infer missing information from a damaged 2D image by tensor voting. Our method translates image color and texture information into an adaptive ND tensor, fol...
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ISBN:
(纸本)0769519008
We present a robust image synthesis method to automatically infer missing information from a damaged 2D image by tensor voting. Our method translates image color and texture information into an adaptive ND tensor, followed by a voting process that infers non-iteratively the optimal color values in the ND texture space for each defective pixel. ND tensor voting can be applied to images consisting of roughly homogeneous and periodic textures (e.g. a brick wall), as well as difficult images of natural scenes, which contain complex color and texture information. To effectively tackle the latter type of difficult images, a two-step method is proposed. First, we perform texture-based segmentation in the input image, and extrapolate partitioning curves to generate a complete segmentation for the image. Then, missing colors are synthesized using ND tensor voting. Automatic tensor scale analysis is used to adapt to different feature scales inherent in the input. We demonstrate the effectiveness of our approach using a difficult set of real images.
Partitioning is a fundamental operation on graphs. In this paper we briefly review the basic concepts of graph partitioning and its relationship to digital mesh processing. We also elaborate on the connection between ...
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Partitioning is a fundamental operation on graphs. In this paper we briefly review the basic concepts of graph partitioning and its relationship to digital mesh processing. We also elaborate on the connection between graph partitioning and spectral graph theory. Applications in computergraphics are described.
A "graphics for vision" approach is proposed to address the problem of reconstruction from a large and imperfect data set: reconstruction on demand by tensor voting, or ROD-TV. ROD-TV simultaneously delivers...
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ISBN:
(纸本)0769519008
A "graphics for vision" approach is proposed to address the problem of reconstruction from a large and imperfect data set: reconstruction on demand by tensor voting, or ROD-TV. ROD-TV simultaneously delivers good efficiency and robustness, by adapting to a continuum of primitive connectivity, view dependence, and levels of detail (LOD). Locally inferred surface elements are robust to noise and better capture local shapes. By inferring per-vertex normals at sub-voxel precision on the fly, we can achieve interpolative shading. Since these missing details can be recovered at the current level of detail, our result is not upper bounded by the scanning resolution. By relaxing the mesh connectivity requirement, we extend ROD-TV and propose a simple but effective multiscale feature extraction algorithm. ROD-TV consists of a hierarchical data structure that encodes different levels of detail. The local reconstruction algorithm is tensor voting. It is applied on demand to the visible subset of data at a desired level of detail, by traversing the data hierarchy and collecting tensorial support in a neighborhood. We compare our approach and present encouraging results.
We explore real time volume rendering of multichannel data for volumes with color and multimodal information. We demonstrate volume rendering of the visible human male color dataset and photorealistic rendering of vox...
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We explore real time volume rendering of multichannel data for volumes with color and multimodal information. We demonstrate volume rendering of the visible human male color dataset and photorealistic rendering of voxelized terrains, and achieve high quality visualizations. We render multimodal volumes utilizing hardware programmability for accumulation level mixing, and use CT and MRI information as examples. We also use multiboard parallel/distributed rendering schemes for large datasets and investigate scalability issues. We employ the VolumePro 1000 for real time multichannel volume rendering. Our approach, however, is not hardware-specific and can use commodity texture hardware instead.
We discuss techniques for the visualization of medical volume data dedicated for their clinical use. We describe the need for rapid dynamic interaction facilities with such visualizations and discuss emphasis techniqu...
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Estimating intrinsic geometric properties of a surface from a polygonal mesh obtained from range data is an important stage of numerous algorithms in computer and robot vision, computergraphics, geometric modeling, i...
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Estimating intrinsic geometric properties of a surface from a polygonal mesh obtained from range data is an important stage of numerous algorithms in computer and robot vision, computergraphics, geometric modeling, industrial and biomedical engineering. This work considers different computational schemes for local estimation of intrinsic curvature geometric properties. Five different algorithms and their modifications were tested on triangular meshes that represent tessellations of synthetic geometric models. The results were compared with the analytically computed values of the Gaussian and mean curvatures of the non-uniform rational B-spline (NURBs) surfaces, these meshes originated from. This work manifests the best algorithms suited for that indeed different algorithms should be employed to compute the Gaussian and mean curvatures.
An experimental study of software image compositing that we have carried out on a 512-node PC cluster shows the necessity of hardware compositing support to make possible real-time volume visualization scalable with l...
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While commodity computing and graphics hardware has increased in capacity and dropped in cost, it is still quite difficult to make effective use of such systems for general-purpose parallel visualization and graphics....
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While commodity computing and graphics hardware has increased in capacity and dropped in cost, it is still quite difficult to make effective use of such systems for general-purpose parallel visualization and graphics. We describe the results of a recent project that provides a software infrastructure suitable for general-purpose use by parallel visualization and graphics applications. Our work combines and extends two technologies: chromium, a stream-oriented framework that implements the OpenGL programming interface; and OpenRM scene graph, a pipelined-parallel scene graph interface for graphics data management. Using this combination, we implement a sort-first, distributed memory, parallel volume rendering application. We describe the performance characteristics in terms of bandwidth requirements and highlight key algorithmic considerations needed to implement the sort-first system. We characterize system performance using a distributed memory parallel volume rendering application, and present performance gains realized by using scene specific knowledge to accelerate rendering by reducing network traffic. The contribution of this work is an exploration of general-purpose, sort-first architecture performance characteristics as applied to distributed memory, commodity hardware, along with a description of the algorithmic support needed to realize parallel, sort-first implementations.
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