RGB相机对三维成像声纳的外部标定

A. Marburg, A. Stewart
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引用次数: 4

摘要

低成本RGB-depth (RGB-D)传感器的引入导致了在受控设置下实现鲁棒3D场景重建的多种算法,但这些算法的水下实现受到大多数RGB-D传感器在水中的受限性能的阻碍。我们探索了将高频机械扫描3D成像声纳生成的点云与摄像机视觉数据融合的可能性,以创建水柱中物体的丰富3D表示。采用了一种最先进的深度传感器-相机配准算法,利用球面目标的并发图像,并将结果对准用于结合声纳和视觉图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extrinsic calibration of an RGB camera to a 3D imaging sonar
The introduction of low-cost RGB-depth (RGB-D) sensors have led to a diversity of algorithms for robust 3D scene reconstruction under controlled settings, but the underwater realization of such algorithms has been hampered by the constrained performance of most RGB-D sensors in water. We explore the possibility of fusing a point cloud generated from a high-frequency, mechanically scanned 3D imaging sonar with visual data from a camera to create a rich 3D representation of objects in the water column. A state-of-the-art algorithm for depth sensor-to-camera registration utilizing concurrent images of spherical targets is adapted, and the resulting alignment is used to combine sonar and visual imagery.
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