Real-Time Markov Chain Path Guiding for Global Illumination and Single Scattering

We present a lightweight and unbiased path guiding algorithm tailored for real-time applications with highly dynamic content. The algorithm demonstrates effectiveness in guiding both direct and indirect illumination. Moreover, it can be extended to guide single scattering events in participating media. Building upon the screen-space approach by Dittebrandt et al. [ 2023 ], the incident light distribution is represented as a von Mises-Fisher mixture model, which is controlled by a Markov chain process. To extend the procedure to world space, our algorithm uses a unique Markov chain architecture, which resamples Markov chain states from an ensemble of hash grids. We combine multi-resolution adaptive grids with a static grid, ensuring rapid state exchange without compromising guiding quality. The algorithm imposes minimal prerequisites on scene representation and seamlessly integrates into existing path tracing frameworks. Through continuous multiple importance sampling, it remains independent of the equilibrium distribution of Markov chain and hash grid resampling. We perform an evaluation of the proposed methods across diverse scenarios. Additionally, we explore the algorithm’s viability in offline scenarios, showcasing its effectiveness in rendering volumetric caustics. We demonstrate the application of the proposed methods in a path tracing engine for the original Quake game. The demo project features path traced global illumination and single scattering effects at frame rates over 30 FPS on NVIDIA’s GeForce 20 series or AMD’s Radeon RX 6000 series without upscaling.