A Theory of Fermat Paths for 3D Imaging Sonar Reconstruction
A Theory of Fermat Paths for 3D Imaging Sonar Reconstruction
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3D 成像声纳重建的费马路径理论
DOI：
10.1109/iros45743.2020.9341613
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
M. Kaess
中科院分区：
文献类型：
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作者：
E. Westman;Ioannis Gkioulekas;M. Kaess
在这项工作中，我们提出了一种利用成像声纳传感器重建特定3D表面点的新方法。我们推导了二维费马流动方程，它可以应用于声纳图像中每个离散方位角所定义的平面。我们证明费马流动方程适用于边界点和表面点，它们对应于由它们的方位角测量定义的2D平面内的镜面反射。费马流方程可以用来求解这些表面点在平面内的2D位置，从而也可以求解它们的全3D位置。这是通过平移传感器来估计距离测量的空间梯度来实现的。该方法不依赖于成像曲面的精确像强值或反射率来求解曲面点位置。我们通过在模拟数据集和真实数据集上重建3D目标点来证明我们所提出的方法的有效性。
In this work, we present a novel method for reconstructing particular 3D surface points using an imaging sonar sensor. We derive the two-dimensional Fermat flow equation, which may be applied to the planes defined by each discrete azimuth angle in the sonar image. We show that the Fermat flow equation applies to boundary points and surface points which correspond to specular reflections within the 2D plane defined by their azimuth angle measurement. The Fermat flow equation can be used to resolve the 2D location of these surface points within the plane, and therefore also their full 3D location. This is achieved by translating the sensor to estimate the spatial gradient of the range measurement. This method does not rely on the precise image intensity values or the reflectivity of the imaged surface to solve for the surface point locations. We demonstrate the effectiveness of our proposed method by reconstructing 3D object points on both simulated and real-world datasets.
DOI：
10.1109/cvpr.2017.251
发表时间：
2017-07
期刊：
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
影响因子：
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作者：
Chia-Yin Tsai;Kiriakos N. Kutulakos;S. Narasimhan;Aswin C. Sankaranarayanan
通讯作者：
Chia-Yin Tsai;Kiriakos N. Kutulakos;S. Narasimhan;Aswin C. Sankaranarayanan