In the context of geometric acoustic simulation, one of the more perceptually important yet difficult to simulate acoustic effects is diffraction, a phenomenon that allows sound to propagate around obstructions and corners. A significant bottleneck in real-time simulation of diffraction is the enumeration of high-order diffraction propagation paths in scenes with complex geometry (e.g. highly tessellated surfaces). To this end, we present a dynamic geometric diffraction approach that consists of an extensive mesh preprocessing pipeline and complementary runtime algorithm. The preprocessing module identifies a small subset of edges that are important for diffraction using a novel silhouette edge detection heuristic. It also extends these edges with planar diffraction geometry and precomputes a graph data structure encoding the visibility between the edges. The runtime module uses bidirectional path tracing against the diffraction geometry to probabilistically explore potential paths between sources and listeners, then evaluates the intensities for these paths using the Uniform Theory of Diffraction. It uses the edge visibility graph and the A* pathfinding algorithm to robustly and efficiently find additional high-order diffraction paths. We demonstrate how this technique can simulate 10th-order diffraction up to 568 times faster than the previous state of the art, and can efficiently handle large scenes with both high geometric complexity and high numbers of sources.

Believable immersive virtual environments require accurate sound in addition to plausible graphics to be convincing to the user. We present a practical and fast method to compute sound reflections for moving sources and listeners in virtual scenes in realtime, even on low end hardware. In a preprocessing step we compute transport paths starting from possible source positions and store virtual diffuse sources along the path. At runtime we connect these subpaths to the actual source position and the virtual diffuse sources to the microphone to compute the impulse response. Our method can be implemented as a single pass GPU rendering process and requires only a few milliseconds for each update.

Abstract In this paper, we extend the concept of pre‐filtered shadow mapping to stochastic rasterization, enabling real‐time rendering of soft shadows from planar area lights. Most existing soft shadow mapping methods lose important visibility information by relying on pinhole renderings from an area light source, providing plausible results only for small light sources. Since we sample the entire 4D shadow light field stochastically, we are able to closely approximate shadows of large area lights as well. In order to efficiently reconstruct smooth shadows from this sparse data, we exploit the analogy of soft shadow computation to rendering defocus blur, and introduce a multiplane pre‐filtering algorithm. We demonstrate how existing pre‐filterable approximations of the visibility function, such as variance shadow mapping, can be extended to four dimensions within our framework.