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Algorithms for Visual Maritime Surveillance with Rapidly Moving Camera.

机译:快速移动摄像机进行海上视觉监视的算法。

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摘要

Visual surveillance in the maritime domain has been explored for more than a decade. Although it has produced a number of working systems and resulted in a mature technology, surveillance has been restricted to the port facilities or areas close to the coastline assuming a fixed-camera scenario. This dissertation presents several contributions in the domain of maritime surveillance. First, a novel algorithm for open-sea visual maritime surveillance is introduced. We explore a challenging situation with a camera mounted on a buoy or other floating platform. The developed algorithm detects, localizes, and tracks ships in the field of view of the camera. Specifically, our method is uniquely designed to handle a rapidly moving camera. Its performance is robust in the presence of a random relatively-large camera motion. In the context of ship detection, a new horizon detection scheme for a complex maritime domain is also developed. Second, the performance of the ship detection algorithm is evaluated on a dataset of 55,000 images. Accuracy of detection of up to 88% of ships is achieved. Lastly, we consider the topic of detection of the vanishing line of the ocean surface plane as a way to estimate the horizon in difficult situations. This allows extension of the ship-detection algorithm to beyond open-sea scenarios.
机译:在海上领域的视觉监视已经探索了十多年。尽管它已经产生了许多工作系统并产生了成熟的技术,但在固定摄像机情况下,监视仅限于港口设施或靠近海岸线的区域。本文提出了在海上监视领域的若干贡献。首先,介绍了一种新颖的海上视觉海上监视算法。我们使用安装在浮标或其他浮动平台上的摄像机来探索具有挑战性的情况。所开发的算法可以检测,定位和跟踪摄像机视场中的船只。具体来说,我们的方法经过独特设计,可以处理快速移动的相机。在随机较大的摄像机运动的情况下,它的性能非常强大。在船舶检测的背景下,还开发了一种用于复杂海域的新的地平线检测方案。其次,在55,000张图像的数据集上评估船舶检测算法的性能。实现了高达88%的船舶检测精度。最后,我们将检测海洋表面消失线这一主题视为在困难情况下估计地平线的一种方法。这允许将舰船检测算法扩展到超出公海场景的范围。

著录项

  • 作者

    Fefilatyev, Sergiy.;

  • 作者单位

    University of South Florida.;

  • 授予单位 University of South Florida.;
  • 学科 Engineering Computer.;Computer Science.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 96 p.
  • 总页数 96
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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