| 研究実績の概要 |
This year, several aspects of acoustic camera sensing in extreme underwater environments were achieved. The first is 3D reconstruction using two to three acoustic images. 3D reconstruction with a small number of acoustic images is a challenging task. An elevation plane sweeping stereo network was proposed. After training the network with a well-built dataset, it is possible to generate high-quality 3D model. This can be applied to underwater monitoring. The second is ground echo modeling, multi-path reflection may influence recognition results using acoustic images. By assuming the ground is flat, it is possible to explicitly model the ground echo. This is an important fundamental research in this field. The third is testing differentiable rendering in acoustic camera. This is the key to building the relationship between image simulation using computer graphics techniques and computer vision tasks like pose estimation and 3D reconstruction. It can be used to solve inverse rendering problems and be integrated into deep learning frameworks. Early results proved the feasibility of the method. A field experiment in water tank was also carried out for dataset collection. Three international conference papers were accepted on the three aspects.
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