论文标题
融合并发的正交宽孔声纳图像，用于密集的水下3D重建
Fusing Concurrent Orthogonal Wide-aperture Sonar Images for Dense Underwater 3D Reconstruction
论文作者
论文摘要
我们提出了一种新型方法，可以处理与前视角多光束成像声纳的观察结果相关的高程角度的歧义，以及进行准确的3D重建所带来的挑战。我们利用一对具有不确定性正交轴的声纳，从两个不同的角度独立观察环境中的相同点，并将这些观察结果相关联。使用这些并发观察，我们可以在每个时间步长创建一个密集的，完全定义的点云，以帮助重建水下场景的3D几何形状。我们将在当前的最新状态下评估我们的方法，为此，对物体几何限制对广义3D场景的限制性限制。我们将讨论实验室测试的结果，这些结果定量基准了我们算法的重建功能，以及来自现实世界中潮汐河盆地的结果，从定性地证明了我们重建水下物体混乱领域的能力。
We propose a novel approach to handling the ambiguity in elevation angle associated with the observations of a forward looking multi-beam imaging sonar, and the challenges it poses for performing an accurate 3D reconstruction. We utilize a pair of sonars with orthogonal axes of uncertainty to independently observe the same points in the environment from two different perspectives, and associate these observations. Using these concurrent observations, we can create a dense, fully defined point cloud at every time-step to aid in reconstructing the 3D geometry of underwater scenes. We will evaluate our method in the context of the current state of the art, for which strong assumptions on object geometry limit applicability to generalized 3D scenes. We will discuss results from laboratory tests that quantitatively benchmark our algorithm's reconstruction capabilities, and results from a real-world, tidal river basin which qualitatively demonstrate our ability to reconstruct a cluttered field of underwater objects.
