Emulating Foveated Path Tracing

Polychronakis, Andrew; Koulieris, George Alex; Mania, Katerina; Boulic, Ronan; Hoyet, Ludovic; Singh, Karan; Rohmer, Damien

Abstract

At full resolution, path tracing cannot be deployed in real-time based on current graphics hardware due to slow convergence times and noisy outputs, despite recent advances in denoisers. In this work, we develop a perceptual sandbox emulating a foveated path tracer to determine the eccentricity angle thresholds that enable imperceptible foveated path tracing. In a foveated path tracer the number of rays fired can be decreased, and thus performance can be increased. For this study, due to current hardware limitations prohibiting real-time path-tracing for multiple samples-per-pixel, we pre-render image buffers and emulate foveated rendering as a post-process by selectively blending the pre-rendered content, driven by an eye tracker capturing eye motion. We then perform three experiments to estimate conservative thresholds of eccentricity boundaries for which image manipulations are imperceptible. Contrary to our expectation of a single threshold across the three experiments, our results indicated three different average thresholds, one for each experiment. We hypothesise that this is due to the dissimilarity of the methodologies, i.e., A-B testing vs sequential presentation vs custom adjustment of eccentricities affecting the perceptibility of peripheral blur among others. We estimate, for the first time for path tracing, specific thresholds of eccentricity that limit any perceptual repercussions whilst maintaining high performance. We perform an analysis to determine potential computational complexity reductions due to foveation in path tracing. Our analysis shows a significant boost in path-tracing performance (≥ 2x − 3x) using our foveated rendering method as a result of the reduction in the primary rays.

Citation

Polychronakis, A., Koulieris, G. A., Mania, K., Boulic, R., Hoyet, L., Singh, K., & Rohmer, D. (2021). Emulating Foveated Path Tracing. In MIG '21: Proceedings of the 14th ACM SIGGRAPH Conference on Motion, Interaction and Games. https://doi.org/10.1145/3487983.3488295

• Conference Name: ACM SIGGRAPH Conference on Motion, Interaction and Games
• Conference Location: Virtual
• Start Date: Nov 10, 2021
• End Date: Nov 12, 2021
• Acceptance Date: Sep 7, 2021
• Online Publication Date: Nov 10, 2021
• Publication Date: Nov 10, 2021
• Deposit Date: Oct 18, 2021
• Publicly Available Date: Nov 13, 2022
• Book Title: MIG '21: Proceedings of the 14th ACM SIGGRAPH Conference on Motion, Interaction and Games
• DOI: https://doi.org/10.1145/3487983.3488295