An adaptive rendering framework for efficient synthetic light field generation

Abstract

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 photo-realistic 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 precomputed and stored in the Cloud. During runtime, the display extracts the color information 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 a good balance between DIBR and Ray Tracing. We study several cases and problems when combing these algorithms and came up with a more efficient solution. 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 reduction. In addition, we also design an efficient multi-threading scheduling to show the scalability of our approach. Experiments show that when the number of threads is small, 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. In the multi-thread environment, our proposed scheme can offer about 2X speedup over traditional ones.