3-D HRTF interpolation
Updated 12 Jan 2015
Matlab demonstration of an algorithm for interpolating distance-dependent (near-field) head-related transfer functions (HRTFs).
The interpolation is performed using barycentric weights of 4 HRTF measurements forming a tetrahedron that encloses the desired source position.
The main steps of the interpolation algorithm are:
1) Initialisation: organise HRTF measurement positions in tetrahedral mesh via Delaunay triangulation and generate an octree;
2) Source update: find a tetrahedron that encloses the desired source position (via brute-force search, or via adjacency walk with/without octree lookup);
3) Interpolation: calculate barycentric weights for linear interpolation of HRTF measurements at the vertices of the tetrahedron selected in 2)
Gamper, H. (2013). "Head-related transfer function interpolation in azimuth, elevation, and distance", Journal of the Acoustical Society of America 134(6), JASA EL547-EL554. Available online: http://link.aip.org/link/?JAS/134/EL547/1
Hannes (2023). 3-D HRTF interpolation (https://www.mathworks.com/matlabcentral/fileexchange/43809-3-d-hrtf-interpolation), MATLAB Central File Exchange. Retrieved .
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- MATLAB > Mathematics > Interpolation >
- Simulink > Simulation >
- Image Processing and Computer Vision > Computer Vision Toolbox > Point Cloud Processing >
- MATLAB > Mathematics > Computational Geometry > Delaunay Triangulation >
Inspired by: octree - partitioning 3D points into spatial subvolumes
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