Acoustic simulation based on multi-view images: A 3DGS-enhanced boundary element method

This study establishes a reconstruction-assisted acoustic simulation workflow for airborne acoustic scattering that links multi-view image reconstruction, geometry post-processing, Catmull–Clark subdivision surface representation, and BEM and FMM-BEM acoustic simulation. In this workflow, 3D Gaussian Splatting (3DGS) and SuGaR are used to obtain an initial explicit geometry from multi-view images. The reconstructed geometry is then post-processed to improve watertightness, normal consistency, and surface smoothness, and it is converted into a Catmull–Clark subdivision surface representation suitable for acoustic BEM. FMM is further used to reduce the cost of large-scale boundary element calculations. Numerical examples on a sphere, an engine model, and a vehicle model verify the underlying BEM formulation, examine reconstructed complex geometries, and compare conventional BEM with FMM-BEM. The results demonstrate the feasibility of converting multi-view reconstructed geometries into watertight and smooth models for acoustic scattering in air, reducing the dependence on manual geometry repair and providing a potential route for future acoustic simulation of measured engineering structures.

Authors

Institutions

Publication Details

Journal
Computers & Mathematics with Applications
Published
2026-10-07
DOI
https://doi.org/10.1016/j.camwa.2026.09.035
Primary Topic
Advanced Numerical Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Acoustic simulation based on multi-view images: A 3DGS-enhanced boundary element method

Haojie Lian, Kui Liu, Jing Zhao, Qingxiang Pei et al.
Computers & Mathematics with Applications
Advanced Numerical Analysis Techniques
article

Acoustic simulation based on multi-view images: A 3DGS-enhanced boundary element method

Haojie Lian, Kui Liu, Jing Zhao, Qingxiang Pei, Mingjing Wang, Wenshuai Zhang
article en

Abstract

This study establishes a reconstruction-assisted acoustic simulation workflow for airborne acoustic scattering that links multi-view image reconstruction, geometry post-processing, Catmull–Clark subdivision surface representation, and BEM and FMM-BEM acoustic simulation. In this workflow, 3D Gaussian Splatting (3DGS) and SuGaR are used to obtain an initial explicit geometry from multi-view images. The reconstructed geometry is then post-processed to improve watertightness, normal consistency, and surface smoothness, and it is converted into a Catmull–Clark subdivision surface representation suitable for acoustic BEM. FMM is further used to reduce the cost of large-scale boundary element calculations. Numerical examples on a sphere, an engine model, and a vehicle model verify the underlying BEM formulation, examine reconstructed complex geometries, and compare conventional BEM with FMM-BEM. The results demonstrate the feasibility of converting multi-view reconstructed geometries into watertight and smooth models for acoustic scattering in air, reducing the dependence on manual geometry repair and providing a potential route for future acoustic simulation of measured engineering structures.

Computers & Mathematics with ApplicationsVol. 224
Harbin Institute of Technology (CN), Huanghuai University (CN), Taiyuan University of Technology (CN)
Openalex Percentile: Top 18%
Advanced Numerical Analysis Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Acoustic simulation based on multi-view images: A 3DGS-enhanced boundary element method — Haojie Lian, Kui Liu, et al. · Computers & Mathematics with Applications (2026) | TGRS Research Map | TGRS