Curvature-adaptive mesh grading for numerical approximation of head-related transfer functions
* Presenting author
Abstract:
Head-related transfer functions (HRTFs) describe the direction dependent sound propagation from a point source to the listeners ears in the free field and are an important tool for virtual and augmented reality applications. Classically, HRTFs are measured acoustically with the listener being positioned in the center of a spherical loudspeaker array. Alternatively, they can be approximated by numerical simulation, for example applying the boundary element method (BEM) to a piecewise linear representation (a surface mesh) of the listener's head. Numerical approximation may be more economical, particularly in combination with methods for the synthesis of head geometry. To decrease the computation time of the BEM, it has been suggested to gradually decrease the resolution of the mesh with increasing distance from the ear for which the HRTF is approximated. We improve this approach by also considering the curvature of the geometry. The resulting graded meshes lead to faster simulation with the same or better accuracy in the HRTF compared to previous work.