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首页> 外文会议>2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems >3D reconstruction of line features using multi-view acoustic images in underwater environment
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3D reconstruction of line features using multi-view acoustic images in underwater environment

机译：在水下环境中使用多视图声像对线要素进行3D重建

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摘要

In order to understand the underwater environment, it is essential to use sensing methodologies able to perceive the three dimensional (3D) information of the explored site. Sonar sensors are commonly employed in underwater exploration. This paper presents a novel methodology able to retrieve 3D information of underwater objects. The proposed solution employs an acoustic camera, which represents the next generation of sonar sensors, to extract and track the line of the underwater objects which are used as visual features for the image processing algorithm. In this work, we concentrate on artificial underwater environments, such as dams and bridges. In these structured environments, the line segments are preferred over the points feature, as they can represent structure information more effectively. We also developed a method for automatic extraction and correspondences matching of line features. Our approach enables 3D measurement of underwater objects using arbitrary viewpoints based on an extended Kalman filter (EKF). The probabilistic method allows computing the 3D reconstruction of underwater objects even in presence of uncertainty in the control input of the camera's movements. Experiments have been performed in real environments. Results showed the effectiveness and accuracy of the proposed solution.
机译：为了了解水下环境，必不可少的是使用能够感知勘探地点的三维（3D）信息的传感方法。声纳传感器通常用于水下勘探。本文提出了一种能够检索水下物体3D信息的新颖方法。所提出的解决方案采用了代表下一代声纳传感器的声学相机来提取和跟踪水下物体的线条，这些线条被用作图像处理算法的视觉特征。在这项工作中，我们专注于人工水下环境，例如水坝和桥梁。在这些结构化的环境中，线段比点特征更可取，因为它们可以更有效地表示结构信息。我们还开发了一种自动提取和匹配线要素的方法。我们的方法基于扩展的卡尔曼滤波器（EKF），可以使用任意视点对水下物体进行3D测量。即使相机运动的控制输入中存在不确定性，该概率方法也可以计算水下物体的3D重建。实验已在真实环境中进行。结果表明了该解决方案的有效性和准确性。

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