![]() ![]() The results of in situ acoustic measurements were used as benchmarks during the calibration process of three-dimensional virtual models. For such a demanding task, efficient calculation schemes and frequency-dependent boundary admittances are implemented in the simulation framework. A representative sample of large coupled-volume opera houses allowed demonstration of the capability of the selected FDTD model to tackle such composite geometries up to 4 kHz. With the aim of testing this potential, this work investigates the feasibility of a finite-difference time-domain (FDTD) code simulating large non-trivial geometries in wide frequency ranges. ![]() Nevertheless, the application field of wave-based simulation methods has been extended in the latest research decades. The constraints are generally the inherent computational cost and the challenging implementation of proper complex boundary conditions. Wave-based techniques for room acoustics simulations are commonly applied to low frequency analysis and small-sized simplified environments. ![]() Results are compared to measurements through calculated reverberant spatial audio object parameters used for reverberation reproduction customized to the given loudspeaker set up. This is, to our knowledge, the first attempt in the literature to use visual geometry estimation and object classification algorithms to predict acoustic properties. The estimated geometry is used to produce frequency-dependent acoustic predictions of the scene. A cuboid-based 3D room geometry model is estimated by correspondence matching between captured images and semantic labelling using a convolutional neural network (SegNet). The scene is captured as a stereo pair using off-the-shelf consumer spherical 360 cameras. We assume that the room and objects can be represented as cuboids aligned to the main axes of the room coordinate (Manhattan world). Instead of setting microphone arrays with loudspeakers to measure acoustic parameters for specific rooms, a simple and practical single-shot capture of the scene using a stereo pair of 360 cameras can be used to simulate those acoustic parameters. In this paper we propose a pipeline for estimating acoustic 3D room structure with geometry and attribute prediction using spherical 360 cameras. ![]()
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February 2023
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