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Forward rasterization: A reconstruction algorithm for image-based rendering.

机译：正向栅格化：一种用于基于图像的渲染的重建算法。

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摘要

In a recent alternative research path for interactive 3D graphics the scene to be rendered is described with images. Image-based rendering (IBR) is appealing since natural scenes, which are very difficult to model conventionally, can be acquired semi-automatically using cameras and other devices. Also IBR has the potential to create high-quality output images if the rendering stage can preserve the quality of the reference images (photographs). One promising IBR approach enhances the images with per-pixel depth. This allows reprojecting or warping the color-and-depth samples from the reference image to the desired image. Image-based rendering by warping (IBRW) is the focus of this dissertation.; In IBRW, simply warping the samples does not suffice for high-quality results because one must reconstruct the final image from the warped samples. This dissertation introduces a new reconstruction algorithm for IBRW. This new approach overcomes some of the major disadvantages of previous reconstruction methods. Unlike the splatting methods, it guarantees surface continuity and it also controls aliasing using a novel filtering method adapted to forward mapping. Unlike the triangle-mesh method, it requires considerably less computation per input sample, reducing the rasterization-setup cost by a factor of four.; The algorithm can be efficiently implemented in hardware and this dissertation presents the WarpEngine, a hardware architecture for IBRW. The WarpEngine consists of several identical nodes that render the frame in a sort-first fashion. Sub-regions of the depth images are processed in parallel in SIMD fashion. The WarpEngine architecture promises to produce high-quality high-resolution images at interactive rates.; This dissertation also analyzes the suitability of our approach for polygon rendering and proposes a possible algorithm for triangles. Finding the samples that must be warped to generate the current frame is another very challenging problem in IBRW. The dissertation introduces the vacuum-buffer sample-selection method, designed to ensure that the set of selected samples covers every visible surface.
机译：在交互式3D图形的最新替代研究路径中，将使用图像描述要渲染的场景。基于图像的渲染（IBR）具有吸引力，因为可以使用相机和其他设备半自动获取传统上很难建模的自然场景。如果渲染阶段可以保留参考图像（照片）的质量，则IBR也有可能创建高质量的输出图像。一种有前途的IBR方法可以按像素深度增强图像。这样就可以将颜色和深度样本从参考图像重新投影或翘曲到所需图像。基于扭曲的图像渲染（IBRW）是本文的重点。在IBRW中，仅对样本进行变形无法满足高质量结果的需要，因为必须从变形的样本中重建最终图像。本文介绍了一种新的IBRW重建算法。这种新方法克服了先前重建方法的一些主要缺点。与 splatting方法不同，它可以保证曲面的连续性，并且还可以使用适用于正向映射的新颖过滤方法来控制锯齿。与三角形网格法不同，它需要每个输入样本更少的计算，从而将光栅化设置成本降低了四倍。该算法可以在硬件中高效实现，本文提出了IBRW的硬件架构。 WarpEngine由几个相同的节点组成，这些节点以优先排序的方式呈现帧。深度图像的子区域以SIMD方式并行处理。 WarpEngine架构有望以交互速率生成高质量的高分辨率图像。本文还分析了我们的多边形渲染方法的适用性，并提出了一种可行的三角形算法。在IBRW中，寻找必须扭曲以生成当前帧的样本是另一个非常具有挑战性的问题。本文介绍了 vacuum-buffer 样本选择方法，该方法旨在确保所选样本集覆盖每个可见表面。

著录项

  • 作者

    Popescu, Voicu Sebastian.;

  • 作者单位

    The University of North Carolina at Chapel Hill.;

  • 授予单位 The University of North Carolina at Chapel Hill.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2001
  • 页码 135 p.
  • 总页数 135
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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