3D reconstruction of underwater scenes using image sequences from acoustic camera

Naouraz Brahim, D. Guériot, Sylvie Daniely, B. Solaiman
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引用次数: 11

Abstract

This paper introduces a system for three-dimensional (3D) reconstruction of underwater environments using multiple images acquired by an acoustical camera from different points of view. The final target of the work is to produce a full 3D representation of the observed environment to improve its exploration and analysis. Indeed, as the DIDSON acoustic camera provides sequences of 2D images (distance and azimuth), the challenge consists in determining the missing elevation information about the observed scene in order to reconstruct (x,y,z) models, together with the geometrical transformation parameters between the acquisition view points, using image information only. Our research work is in its early stage, the work presented in this paper is particularly focused on the first step of the 3D reconstruction system which is feature point extraction as feature points must represent the scene geometrical characteristics. Thus, the proposed methodology is based on corner detection from extracted contours. However, speckle noise introduces local, non-geometrically relevant contours that should be removed. Embedded within a multi-scale edge analysis approach, analyzing extracted contours from several consecutive images allows relevant contours selection. This methodology applied to real and simulated images, shows promising results to complete the full 3D reconstruction process.
利用声学相机图像序列进行水下场景的三维重建
本文介绍了一种利用声学摄像机从不同视点获取的多幅图像对水下环境进行三维重建的系统。这项工作的最终目标是生成观察环境的完整3D表示,以改进其探索和分析。事实上,由于DIDSON声学相机提供了2D图像序列(距离和方位角),因此挑战在于确定观测场景中缺失的仰角信息,以便仅使用图像信息重建(x,y,z)模型,以及采集视点之间的几何转换参数。我们的研究工作还处于初级阶段,本文的工作主要集中在三维重建系统的第一步,即特征点的提取,因为特征点必须代表场景的几何特征。因此,所提出的方法是基于提取轮廓的角点检测。然而,散斑噪声引入了局部的,非几何相关的轮廓,应该被去除。嵌入在多尺度边缘分析方法中,分析从几个连续图像中提取的轮廓可以选择相关的轮廓。该方法应用于真实和模拟图像,显示出有希望的结果,以完成完整的三维重建过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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