论文标题

片段历史的体积

Fragment-History Volumes

论文作者

Inácio, Francisco, Springer, Jan P.

论文摘要

基于硬件的三角栅格化仍然是在实时交互式帧速率下生成图像的普遍方法。借助可编程图形管道的可用性,支持多种技术来评估碎片的照明和材料特性。但是,这些技术通常仅限于评估局部照明和物质影响。此外,视图更改需要完整的场景数据处理以生成适当的图像。通过扭曲新的观点来重用帧缓冲区中已经在框架缓冲区中渲染的数据,以增加导航保真度,而牺牲了以前从查看器隐藏的片段引入片段。 我们提出了片段历史的体积(FHV),这是一种基于3D场景的稀疏,离散的表示的渲染技术,它是由于记录所有通过图形管道中的栅格化阶段的片段而出现的。这些片段存储在每个像素或每一个列表中,以进行进一步处理。本质上是创建一个屁股。使用每位片段列表的FHV是独立的视图,并允许快速重新采样图像生成以及使用更复杂的方法评估材料和照明属性,最终在当前硬件上可用的标准图形管道中实现了全局刷新评估。 我们展示了如何以多种方式将FHV存储在GPU上,如何创建它们以及如何以高速率用于图像生成。我们讨论了不同使用方案,技术变化以及一些局限性的结果。

Hardware-based triangle rasterization is still the prevalent method for generating images at real-time interactive frame rates. With the availability of a programmable graphics pipeline a large variety of techniques are supported for evaluating lighting and material properties of fragments. However, these techniques are usually restricted to evaluating local lighting and material effects. In addition, view-point changes require the complete processing of scene data to generate appropriate images. Reusing already rendered data in the frame buffer for a given view point by warping for a new viewpoint increases navigation fidelity at the expense of introducing artifacts for fragments previously hidden from the viewer. We present fragment-history volumes (FHV), a rendering technique based on a sparse, discretized representation of a 3d scene that emerges from recording all fragments that pass the rasterization stage in the graphics pipeline. These fragments are stored into per-pixel or per-octant lists for further processing; essentially creating an A-buffer. FHVs using per-octant fragment lists are view independent and allow fast resampling for image generation as well as for using more sophisticated approaches to evaluate material and lighting properties, eventually enabling global-illumination evaluation in the standard graphics pipeline available on current hardware. We show how FHVs are stored on the GPU in several ways, how they are created, and how they can be used for image generation at high rates. We discuss results for different usage scenarios, variations of the technique, and some limitations.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源