Neural Implicit Surface Reconstruction using Imaging Sonar

• URL: http://arxiv.org/abs/2209.08221v1
• Date: Sat, 17 Sep 2022 02:23:09 GMT
• Title: Neural Implicit Surface Reconstruction using Imaging Sonar
• Authors: Mohamad Qadri, Michael Kaess, Ioannis Gkioulekas
• Abstract summary: We present a technique for dense 3D reconstruction of objects using an imaging sonar, also known as forward-looking sonar (FLS) Compared to previous methods that model the scene geometry as point clouds or volumetric grids, we represent geometry as a neural implicit function. We perform experiments on real and synthetic datasets and show that our algorithm reconstructs high-fidelity surface geometry from multi-view FLS images at much higher quality than was possible with previous techniques and without suffering from their associated memory overhead.
• Score: 38.73010653104763
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a technique for dense 3D reconstruction of objects using an imaging sonar, also known as forward-looking sonar (FLS). Compared to previous methods that model the scene geometry as point clouds or volumetric grids, we represent the geometry as a neural implicit function. Additionally, given such a representation, we use a differentiable volumetric renderer that models the propagation of acoustic waves to synthesize imaging sonar measurements. We perform experiments on real and synthetic datasets and show that our algorithm reconstructs high-fidelity surface geometry from multi-view FLS images at much higher quality than was possible with previous techniques and without suffering from their associated memory overhead.

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