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Data-driven volumetric reconstruction for optically measured sound field using physics-constrained 3D Gaussian
Risako Tanigawa1,2, Kenji Ishikawa1, Noboru Harada1
1Communication Science Laboratories, NTT, Inc., Atsugi, Kanagawa 243-0198, Japan.
The Journal of the Acoustical Society of America
|September 17, 2025
Summary
A novel data-driven method using 3D Gaussian splatting reconstructs complex sound fields from acousto-optic sensing data. This approach overcomes limitations of traditional methods, enabling accurate sound field mapping.
Area of Science:
- Acoustics
- Computer Vision
- Signal Processing
Background:
- Acousto-optic sensing offers high-resolution sound measurement but faces challenges due to line integral data.
- Existing physical-model-based reconstruction methods are limited by basis function choices, restricting their applicability to diverse sound fields.
Purpose of the Study:
- To develop a data-driven sound-field reconstruction method capable of handling high-complexity sound fields.
- To adapt and extend the 3D Gaussian splatting (3DGS) technique for accurate three-dimensional (3D) sound field reconstruction.
Main Methods:
- Leveraged a 3D Gaussian splatting (3DGS) scheme, a computer vision technique representing scenes with Gaussian kernels.
- Extended the R2-Gaussian volume reconstruction approach to accommodate arbitrary real numbers for sound field representation.
- Incorporated a Helmholtz loss function into the optimization process for improved reconstruction accuracy.
Main Results:
- The proposed 3DGS-based method, R2-Gaussian, demonstrated successful reconstruction of sound fields.
- Evaluations included 11 simulated and 1 measured sound field, validating the approach's effectiveness across various scenarios.
- The data-driven nature allows for greater flexibility compared to traditional basis function-dependent models.
Conclusions:
- The 3DGS-based data-driven approach offers a powerful solution for reconstructing complex 3D sound fields.
- This method overcomes limitations of traditional techniques, paving the way for more versatile acousto-optic sensing applications.
- Future work may explore further optimizations and real-world deployment of this advanced sound field reconstruction technique.
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