首页> 外文会议>OCEANS 2012 MTS/IEEE Yeosu >Indexing and selection of well-lit details in underwater video mosaics using vignetting estimation
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Indexing and selection of well-lit details in underwater video mosaics using vignetting estimation

机译:使用渐晕估计来索引和选择水下视频马赛克中光线充足的细节

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Video is an important tool in underwater surveys today, yet its useful field of view is restricted to image details within well lit regions on the seafloor. In this paper we present a novel vignetting-based weighting scheme for selecting these well lit details for use in the creation of a wide area view (mosaic) of the surveyed seafloor. Apart from this detail selection novelity, two other contributions are made. Firstly, because some of these scenes contain very little image texture, we introduce a hybrid homography estimation procedure that uses both feature-based and exhaustive searching techniques. Secondly, to facilitate cross referencing with the video, sections of the mosaic were indexed with the frame number in which the respective image details was selected from. We test our algorithm with real seabed survey video, whose scientific mission was population census of the particular species of lobster, Nephrops norvegicus. High quality mosaics were obtained that captured image details from well lit regions of the scene, which expert marine biologists agreed was a useful analysis tool.
机译:视频是当今水下调查的重要工具,但其有用的视野仅限于海底光线充足区域内的图像细节。在本文中,我们提出了一种新颖的基于渐晕的加权方案,用于选择这些光线充足的细节,以用于创建被调查海床的广域视图(马赛克)。除了这种细节选择的新颖性之外,还做出了另外两个贡献。首先,由于这些场景中的某些场景包含很少的图像纹理,因此我们引入了混合单应性估计过程,该过程同时使用基于特征的搜索和详尽的搜索技术。其次,为了便于与视频进行交叉引用,以从其中选择了各个图像细节的帧编号来索引马赛克的各个部分。我们用真实的海床调查视频测试了我们的算法,该视频的科学任务是对龙虾Nephrops norvegicus的特定物种进行人口普查。获得了高质量的马赛克,可以捕获场景中光线充足的区域中的图像细节,海洋生物学专家认为这是有用的分析工具。

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