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.
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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ISBN:
(纸本)1581137451
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 large PC clusters. This paper describes the design and performance evaluation of such a hardware image compositing device. A PC cluster using such devices along with commodity graphics cards can enable simultaneous simulation and volume visualization.
Texture mapping has become indispensable in image synthesis as an inexpensive source of rich visual detail. Less obvious, but just as useful, is its ability to mask image errors due to inaccuracies in geometry or ligh...
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Texture mapping has become indispensable in image synthesis as an inexpensive source of rich visual detail. Less obvious, but just as useful, is its ability to mask image errors due to inaccuracies in geometry or lighting. This ability can be used to substantially accelerate rendering by eliminating computations when the resulting errors will be perceptually insignificant. Our new method precomputes the masking ability of textures using aspects of the JPEG image compression standard. This extra information is stored as threshold elevation factors in the texture's mip-map and interpolated at image generation time as part of the normal texture lookup process. Any algorithm which uses error tolerances or visibility thresholds can then take advantage of texture masking. Applications to adaptive shadow testing, irradiance caching, and path tracing are demonstrated. Unlike prior methods, our approach does not require that initial images be computed before masking can be exploited and incurs only negligible runtime computational overhead. Thus, it is much easier to integrate with existing rendering systems for both static and dynamic scenes and yields computational savings even when only small amounts of texture masking are present. Categories and Subject Descriptors (according to ACM CCS): I.3.7 [computergraphics]: Color, shading, shadowing, and texture
Displacement mapping is a technique for applying fine geometric detail to a simpler base surface. The displacement is often specified as a scalar function which makes it relatively easy to increase visual complexity w...
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Displacement mapping is a technique for applying fine geometric detail to a simpler base surface. The displacement is often specified as a scalar function which makes it relatively easy to increase visual complexity without the difficulties inherent in more general modeling techniques. We would like to use displacement mapping in real-time applications. Ideally, a graphics accelerator should create a polygonal tessellation of the displaced surface on the fly to avoid storage and host bandwidth overheads. We present an online, adaptive, crack-free tessellation scheme for real-time displacement mapping that uses only local information for each triangle to perform a view-dependent tessellation. The tessellation works in homogeneous coordinates and avoids re-transformation of displaced points, making it suitable for high-performance hardware implementation. The use of interval analysis produces meshes with good error bounds that converge quickly to the true surface.
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