Brand new GPU path tracing research from Nvidia and AMD

Abstract 

We introduce gradient-domain rendering for Monte Carlo image synthesis. While previous gradient-domain Metropolis Light Transport sought to distribute more samples in areas of high gradients, we show, in contrast, that estimating image gradients is also possible using standard (non-Metropolis) Monte Carlo algorithms, and furthermore, that even without changing the sample distribution, this often leads to significant error reduction. This broadens the applicability of gradient rendering considerably. To gain insight into the conditions under which gradient-domain sampling is beneficial, we present a frequency analysis that compares Monte Carlo sampling of gradients followed by Poisson reconstruction to traditional Monte Carlo sampling. Finally, we describe Gradient-Domain Path Tracing (G-PT), a relatively simple modification of the standard path tracing algorithm that can yield far superior results. 

Abstract 

Physically correct rendering of environment illumination has been a long-standing challenge in interactive graphics, since Monte-Carlo ray-tracing requires thousands of rays per pixel. We propose accurate filtering of a noisy Monte-Carlo image using Fourier analysis. Our novel analysis extends previous works by showing that the shape of illumination spectra is not always a line or wedge, as in previous approximations, but rather an ellipsoid. Our primary contribution is an axis-aligned filtering scheme that preserves the frequency content of the illumination. We also propose a novel application of our technique to mixed reality scenes, in which virtual objects are inserted into a real video stream so as to become indistinguishable from the real objects. The virtual objects must be shaded with the real lighting conditions, and the mutual illumination between real and virtual objects must also be determined. For this, we demonstrate a novel two-mode path tracing approach that allows ray-tracing a scene with image-based real geometry and mesh-based virtual geometry. Finally, we are able to de-noise a sparsely sampled image and render physically correct mixed reality scenes at over 5 fps on the GPU.

While Nvidia is certainly at the forefront of GPU path tracing research (with CUDA), AMD has recently begun venturing into GPU rendering as well and has previewed its own OpenCL based path tracer at the Siggraph 2014 conference. The path tracer is developed by Takahiro Harada, who is a bit of an OpenCL rendering genius. He recently published an article in GPU Pro 6 about rendering on-the-fly vector displacement mapping with OpenCL based GPU path tracing. Vector displacement mapping differs from regular displacement mapping in that it allows the extrusion of overlapping geometry (eg a mushroom), which is not possible with the heightfield-like displacement provided by traditional displacement (the Renderman vector displacement documentation explains this nicely with pictures).

Slides from http://www.slideshare.net/takahiroharada/introduction-to-monte-carlo-ray-tracing-opencl-implementation-cedec-2014:

This video shows off the new technique, rendering in near-realtime on the GPU:

There's more info on Takahiro's personal page, along with some really interesting slideshow presentations about OpenCL based ray tracing. This guy also developed a new technique called "Foveated real-time ray tracing for virtual reality devices" (paper), progressively focusing more samples on the parts in the image where the eyes are looking (determined by eye/pupil tracking), "reducing the number of pixels to shade by 1/20, achieving 75 fps while preserving the same visual quality" (source: http://research.lighttransport.com/foveated-real-time-ray-tracing-for-virtual-reality-headset/asset/abstract.pdf). Foveated rendering takes advantage of the fact that the human retina is most sensitive in its center (the "fovea", which contains densely packed colour sensitive cones) where objects' contours and colours are sharply observed, while the periphery of the retina consists mostly of sparsely distributed, colour insensitive rods, which cause objects in the periphery of the visual field to be represented by the brain as blurry blobs (although we do not consciously perceive it like that, thinking that our entire visual field is sharply defined and has colour).

This graph shows that the resolution of the retina is highest at the fovea and drops off quickly with increasing distance from the center. This is due to the fact that the fovea contains only cones which each send individual inputs over the optic fibre (maximizing resolution), while the inputs from several rods in the periphery of the retina are merged by the retinal nerve cells before reaching the optic nerve (image from www.telescope-optics.net/eye.htm):

Foveated rendering has the potential to make high quality real-time raytraced imagery feasible on VR headsets that support eye tracking like the recently Kickstarted FOVE VR headset. Using ray tracing for foveated rendering is also much more efficient than using rasterisation: ray tracing allows for sparse loading and sampling of the scene geometry in the periphery of the visual field, while rasterisation needs to load and project all geometry in the viewplane, whether it's sampled or not.

Slides from www.slideshare.net/takahiroharada/foveated-ray-tracing-for-vr-on-multiple-gpus

This video shows a working prototype of the FOVE VR headset with a tracking beam to control which parts of the scene are in focus, so this type of real-time ray traced (or path traced) foveated rendering should be possible right now, (which is pretty exciting):