Rail-Track Viewer - An Image-Based Virtual Walkthrough System

Lining Yang, R. Crawfis
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引用次数: 13

Abstract

Complex renderings of synthetic scenes or virtual environments, once deemed impossible for consumer rendering, are becoming available as tools for young artists. These renderings, due to their high-quality image synthesis, can take minutes to hours to render. Nowadays, as the computing power has increased dramatically, the size and complexity of the datasets generated by the super-computer can be overwhelming. It is almost impossible for the visualization techniques to achieve interactive frame rates. Our work focuses on using Image-Based Rendering (IBR) techniques to manage and explore large and complex datasets and virtual scenes on a remote display across the world-wide-web. The key idea for this research is to pre-process the datasets and render key viewpoints on pre-selected paths inside the dataset. We present new techniques to reconstruct approximations to any view along the path, which allows the user to roam around inside the datasets with interactive frame rates. We have implemented the pipeline for generating the sampled key viewpoints and reconstructing panoramic-based IBR models. Our implementation includes an efficient two-phase caching and pre-fetching scheme. The system has been successfully tested on several datasets and satisfying results have been obtained. Analysis of errors is also presented.
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铁路轨道查看器-基于图像的虚拟演练系统
合成场景或虚拟环境的复杂渲染,曾经被认为是不可能的消费者渲染,正成为年轻艺术家可用的工具。这些效果图,由于其高质量的图像合成,可能需要几分钟到几个小时来渲染。如今,随着计算能力的急剧增加,超级计算机生成的数据集的大小和复杂性可能是压倒性的。可视化技术几乎不可能实现交互帧率。我们的工作重点是使用基于图像的渲染(IBR)技术来管理和探索大型和复杂的数据集和虚拟场景在一个远程显示跨万维网。本研究的关键思想是对数据集进行预处理,并在数据集中预先选择的路径上呈现关键视点。我们提出了新的技术来重建沿着路径的任何视图的近似值,这允许用户在具有交互帧率的数据集中漫游。我们实现了生成采样关键视点和重建基于全景的IBR模型的流水线。我们的实现包括一个高效的两阶段缓存和预取方案。该系统已在多个数据集上进行了测试,取得了满意的结果。并对误差进行了分析。
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