Parametric Directional Coding for Precomputed Sound Propagation

ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH 2018 | , Vol 37(4)

DOI

Convincing audio for games and virtual reality requires modeling directional propagation effects. The initial sound’s arrival direction is particularly salient and derives from multiply-diffracted paths in complex scenes. When source and listener straddle occluders, the initial sound and multiply-scattered reverberation stream through gaps and portals, helping the listener navigate. Geometry near the source and/or listener reveals its presence through anisotropic reflections. We propose the first precomputed wave technique to capture such directional effects in general scenes comprising millions of polygons. These effects are formally represented with the 9D directional response function of 3D source and listener location, time, and direction at the listener, making memory use the major concern. We propose a novel parametric encoder that compresses this function within a budget of ~100MB for large scenes, while capturing many salient acoustic effects indoors and outdoors. The encoder is complemented with a lightweight signal processing algorithm whose filtering cost is largely insensitive to the number of sound sources, resulting in an immediately practical system.

Parametric Directional Coding for Precomputed Sound Propagation

Convincing audio for games and virtual reality requires modeling directional propagation effects. The initial sound's arrival direction is particularly salient and derives from multiply-diffracted paths in complex scenes. When source and listener straddle occluders, the initial sound and multiply-scattered reverberation stream through gaps and portals, helping the listener navigate. Geometry near the source and/or listener reveals its presence through anisotropic reflections. We propose the first precomputed wave technique to capture such directional effects in general scenes comprising millions of polygons. These effects are formally represented with the 9D directional response function of 3D source and listener location, time, and direction at the listener, making memory use the major concern. We propose a novel parametric encoder that compresses this function within a budget of ~100MB for large scenes, while capturing many salient acoustic effects indoors and outdoors. The encoder is complemented with a lightweight signal processing algorithm whose filtering cost is largely insensitive to the number of sound sources, resulting in an immediately practical system.