高效合成光场生成使用自适应多层次渲染

Liang-Chi Tseng, W. Hsu
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引用次数: 0

摘要

实时全局照明渲染对于虚拟现实(VR)和增强现实(AR)等新兴应用是非常理想的。然而,由于计算资源不足,客户端设备在支持光线追踪等逼真渲染方面存在困难。许多现代框架采用光场渲染来支持设备显示。光场可以预先计算并存储在云中。在运行时,显示器从光场中提取颜色以生成任意的实时视点或在预定义区域内重新聚焦。为了有效地计算光场,我们以自适应的方式将DIBR (deep - image - based rendering)和传统的光线追踪相结合来合成图像。通过测量运行时的颜色误差,自适应地确定DIBR和光线追踪之间的正确平衡。为了进一步优化计算效率,我们还增加了多级设计,利用图像之间可共享像素的程度来控制误差去除的计算。实验表明,对于相对简单的场景(如Cornell Box),我们实现了高达3.24倍的光场生成加速,对于复杂的场景(如Conference Room或Sponza),我们实现了大约2倍的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient synthetic light field generation using adaptive multi-level rendering
Real-time global illumination rendering is very desirable for emerging applications such as Virtual Reality (VR) and Augmented Reality (AR). However, client devices have difficulties to support photorealistic rendering, such as Ray-Tracing, due to insufficient computing resources. Many modern frameworks adopted Light Field rendering to support device displaying. A Light Field can be pre-computed and store in cloud. During runtime, the display extracts the colors from the Light Field to generate arbitrary real time viewpoints or re-focusing within a predefined area. To efficiently compute the Light Field, We have combined DIBR (Depth-Image-Based-Rendering) and traditional ray-tracing in an adaptive fashion to synthesize images. By measuring the color errors during runtime, we adaptively determine the right balance between DIBR and Ray Tracing. To further optimize the computation efficiency, we also added a multi-level design to exploit the degree of shareable pixels among images to control the computation for error removal. Experiments show that we achieved up to 3.24X speedup in Light Field generation for relative simple scenes like Cornell Box, and about 2X speed up for complex scenes like Conference Room or Sponza.
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