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首页> 外文期刊>Journal of Mechanical Science and Technology >3D reconstruction of underwater scene for marine bioprospecting using remotely operated underwater vehicle (ROV)
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3D reconstruction of underwater scene for marine bioprospecting using remotely operated underwater vehicle (ROV)

机译:使用远程运行的水下车辆进行海洋生物锚定水下场景的三维重建(ROV)

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摘要

Marine bioprospecting is the procedure of identifying the characteristics of marine organisms to develop them into commercial products. This paper proposes a 3D reconstruction algorithm to facilitate 3D visualization of underwater scene for the marine bioprospecting using remotely operated underwater vehicle (ROV). It allows to provide an operator with intuitive user interface and accordingly contribute to enhance the operability of the ROV in the bioprospecting operation. The reconstruction algorithm transforms 2D pixel coordinates of the sonar image into the corresponding 3D spatial coordinates of the scene surface by restoring the surface elevation missing in the sonar image. First, the algorithm segments the objects and shadows in the image by classifying the pixels based on the intensity value of the seafloor. Second, it computes the surface elevation on the object pixels based on their intensity values. Third, the elevation correction factor, which is derived by the ratio between height of the object and the length of the shadow, is multiplied to the surface elevation value. Finally, the 3D coordinates of the scene surfaces are reconstructed using the coordinate transformation from the image plane to the seafloor with the restored surface elevation values. The experimental results show the algorithm successfully reconstructs the surface of the reference object within an error range less than 10 % of the object dimension, and practical applicability to the marine bioprospecting operation.
机译:海洋生物勘探是识别海洋生物的特征,将其开发成商业产品的过程。本文提出了一种三维重建算法,以便于利用遥控水下机器人(ROV)进行海洋生物勘探的水下场景的三维可视化。它可以为操作员提供直观的用户界面,从而有助于提高ROV在生物勘探操作中的可操作性。重建算法通过恢复声纳图像中缺失的表面高程,将声纳图像的二维像素坐标转换为场景表面的相应三维空间坐标。首先,该算法根据海底的强度值对像素进行分类,对图像中的物体和阴影进行分割。其次,它根据对象像素的强度值计算其表面高程。第三,将由对象高度和阴影长度之间的比率导出的高程修正系数乘以曲面高程值。最后,使用从图像平面到海底的坐标变换以及恢复的表面高程值,重建场景表面的三维坐标。实验结果表明,该算法能在小于目标尺寸10%的误差范围内成功地重建参考目标的表面,适用于海洋生物勘探作业。

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