Path tracing is one of the most widespread rendering techniques for high-end graphics fidelity. However, the slow convergence time and presence of intensive noises make it infeasible for numerous real-time applications where physically corrected photorealistic effects are salient. Additionally, the increased demand for pixel density, geometric complexity, advanced material, and multiple lights hinder the algorithm from attaining an interactive frame rate for real-time applications. To address these issues, we developed a framework to accelerate path tracing through foveated rendering, a robust technique that leverages human vision. Our dynamic foveated path-tracing framework integrates fixation data and selectively lowers the rendering resolution towards the periphery. The framework is built on NVIDIA's OptiX 7.5 API with CUDA 12.1, serving as the base of future foveated path tracing research. Through comprehensive experimentation, we demonstrated the effectiveness of our framework in this paper. Depending on the scene complexity, our solution can significantly enhance rendering performance up to a factor of 25 without any notable visual differences. We further evaluated the framework using a structured error map algorithm with variable sample numbers and foveated area size.

翻译：路径追踪是实现高端图形保真度最广泛的渲染技术之一。然而，其缓慢的收敛速度与密集噪声的存在，使其难以应用于众多对物理校正的光照真实感效果有突出需求的实时应用场景。此外，日益增长的像素密度、几何复杂度、高级材质及多光源需求，进一步阻碍了该算法在实时应用中达到交互式帧率。为解决这些问题，我们开发了一个通过注视点渲染加速路径追踪的框架，该技术是一种利用人类视觉特性的鲁棒方法。我们的动态注视点路径追踪框架整合了注视点数据，并选择性降低外围区域的渲染分辨率。该框架基于NVIDIA的OptiX 7.5 API与CUDA 12.1构建，为未来注视点路径追踪研究奠定了基础。通过全面实验，我们在本文中验证了该框架的有效性。根据场景复杂度，我们的解决方案可将渲染性能显著提升最高达25倍，且不会产生明显的视觉差异。我们进一步采用可变采样数与注视区域尺寸的结构化误差图算法对该框架进行了评估。