论文标题
Cinema Darkroom:大规模数据集的递延渲染框架
Cinema Darkroom: A Deferred Rendering Framework for Large-Scale Datasets
论文作者
论文摘要
本文提出了一个框架,该框架完全利用了延期渲染方法的优势,用于大规模数据集的交互式可视化。几何缓冲液(G-Buffer)是生成并原位存储的,并在基于交互式图像的渲染前端进行阴影进行了阴影。这个脱钩的框架具有两个主要优势。首先,只需要计算和存储一次G-buffer,这与渲染管道最昂贵的部分相对应。其次,稍后可以在基于图像的前端消耗存储的G-buffers,该渲染前端可以使用户可以交互调整各种可视化参数 - 例如应用的颜色图或环境闭塞的强度 - 通常不知道合适的选择。本文展示了在几个现实世界数据集中使用Cinema Darkroom的使用,突出了CD有效地将数据集的复杂性和大小从其可视化中解脱出来的能力。
This paper presents a framework that fully leverages the advantages of a deferred rendering approach for the interactive visualization of large-scale datasets. Geometry buffers (G-Buffers) are generated and stored in situ, and shading is performed post hoc in an interactive image-based rendering front end. This decoupled framework has two major advantages. First, the G-Buffers only need to be computed and stored once---which corresponds to the most expensive part of the rendering pipeline. Second, the stored G-Buffers can later be consumed in an image-based rendering front end that enables users to interactively adjust various visualization parameters---such as the applied color map or the strength of ambient occlusion---where suitable choices are often not known a priori. This paper demonstrates the use of Cinema Darkroom on several real-world datasets, highlighting CD's ability to effectively decouple the complexity and size of the dataset from its visualization.