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An Alignment Method for the Integration of Underwater 3D Data Captured by a Stereovision System and an Acoustic Camera

机译:一种将立体视觉系统和声像仪捕获的水下3D数据进行整合的对准方法

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摘要

The integration of underwater 3D data captured by acoustic and optical systems is a promising technique in various applications such as mapping or vehicle navigation. It allows for compensating the drawbacks of the low resolution of acoustic sensors and the limitations of optical sensors in bad visibility conditions. Aligning these data is a challenging problem, as it is hard to make a point-to-point correspondence. This paper presents a multi-sensor registration for the automatic integration of 3D data acquired from a stereovision system and a 3D acoustic camera in close-range acquisition. An appropriate rig has been used in the laboratory tests to determine the relative position between the two sensor frames. The experimental results show that our alignment approach, based on the acquisition of a rig in several poses, can be adopted to estimate the rigid transformation between the two heterogeneous sensors. A first estimation of the unknown geometric transformation is obtained by a registration of the two 3D point clouds, but it ends up to be strongly affected by noise and data dispersion. A robust and optimal estimation is obtained by a statistical processing of the transformations computed for each pose. The effectiveness of the method has been demonstrated in this first experimentation of the proposed 3D opto-acoustic camera.
机译:由声学和光学系统捕获的水下3D数据的集成在各种应用(例如地图绘制或车辆导航)中是一种很有前途的技术。它可以弥补声学传感器分辨率低的缺点以及在可见性差的情况下光学传感器的局限性。对齐这些数据是一个具有挑战性的问题,因为很难进行点对点的对应。本文提出了一种多传感器配准,用于在近距离采集中自动集成从立体视觉系统和3D声学相机采集的3D数据。在实验室测试中已使用适当的钻机确定两个传感器框架之间的相对位置。实验结果表明,我们的对准方法基于在几个姿势下获取钻机,可以用来估计两个异构传感器之间的刚性转换。通过两个3D点云的配准获得了未知几何变换的第一估计,但是最终受到噪声和数据分散的强烈影响。通过对为每个姿势计算的变换进行统计处理,可以获得鲁棒且最佳的估计。该方法的有效性已在建议的3D光声相机的首次实验中得到了证明。

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