Integration of Motion Cues in Optical and Sonar Videos for 3-D Positioning

S. Negahdaripour, H. Pirsiavash, H. Sekkati
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引用次数: 9

Abstract

Target-based positioning and 3-D target reconstruction are critical capabilities in deploying submersible platforms for a range of underwater applications, e.g., search and inspection missions. While optical cameras provide high-resolution and target details, they are constrained by limited visibility range. In highly turbid waters, target at up to distances of 10 s of meters can be recorded by high-frequency (MHz) 2-D sonar imaging systems that have become introduced to the commercial market in years. Because of lower resolution and SNR level and inferior target details compared to optical camera in favorable visibility conditions, the integration of both sensing modalities can enable operation in a wider range of conditions with generally better performance compared to deploying either system alone. In this paper, estimate of the 3-D motion of the integrated system and the 3-D reconstruction of scene features are addressed. We do not require establishing matches between optical and sonar features, referred to as opti-acoustic correspondences, but rather matches in either the sonar or optical motion sequences. In addition to improving the motion estimation accuracy, advantages of the system comprise overcoming certain inherent ambiguities of monocular vision, e.g., the scale-factor ambiguity, and dual interpretation of planar scenes. We discuss how the proposed solution provides an effective strategy to address the rather complex opti-acoustic stereo matching problem. Experiment with real data demonstrate our technical contribution.
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运动线索在光学和声纳视频中的集成用于三维定位
基于目标的定位和三维目标重建是部署潜水平台进行一系列水下应用的关键能力,例如搜索和检查任务。虽然光学相机提供高分辨率和目标细节,但它们受到有限的可见范围的限制。在高度浑浊的水域中,高频(MHz)二维声纳成像系统可以记录距离达10米的目标,该系统多年来已被引入商业市场。由于在有利的能见度条件下,与光学相机相比,分辨率和信噪比较低,目标细节较差,因此与单独部署任一系统相比,两种传感模式的集成可以在更广泛的条件下运行,并且通常具有更好的性能。本文主要研究了集成系统的三维运动估计和场景特征的三维重建。我们不需要在光学和声纳特征之间建立匹配,称为光声对应,而是在声纳或光学运动序列中建立匹配。除了提高运动估计精度外,该系统的优点还包括克服了单目视觉固有的某些模糊性,例如比例因子模糊性和平面场景的双重解释。我们讨论了所提出的解决方案如何提供一个有效的策略来解决相当复杂的光声立体匹配问题。实际数据实验证明了我们的技术贡献。
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