Stabilizing Image Mosaicing by Model Selection

机译：通过模型选择稳定图像拼接

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The computation for image mosaicing using homographies is numerically unstable and causes large image distortions if the matching points are small in number and concentrated in a small region in each image. This instability stems from the fact that actual transformations of images are usually in a small subgroup of the group of homographies. It is shown that such undesirable distortions can be removed by model selection using the geometric AIC without introducing any empirical thresholds. It is shown that the accuracy of image mosaicing can be improved beyond the theoretical bound imposed on statistical optimization. This is made possible by our knowledge about probable subgroups of the group of homographies. We demonstrate the effectiveness of our method by real image examples.

机译：如果匹配点的数量少并且集中在每个图像的较小区域中，则使用单应性进行图像拼接的计算在数值上是不稳定的，并且会导致较大的图像失真。这种不稳定性源于这样一个事实，即图像的实际变换通常在同形异义词组的一小部分中。结果表明，可以通过使用几何AIC进行模型选择来消除这种不希望的失真，而无需引入任何经验阈值。结果表明，图像拼接的精度可以提高到超出统计优化的理论范围。这是由于我们对单应群的可能子群的了解而实现的。我们通过真实的图像示例证明了我们方法的有效性。

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《Second European Workshop on 3D Structure from Multiple Images of Large-Scale Environments, Jul 1-2, 2000, Dublin, Irleand》|2000年|p.35-51|共17页
会议地点 Dublin(IE);Dublin(IE)
作者
Yasushi Kanazawa; Kenichi Kanatani;
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Department of Knowledge-based Information Engineering Toyohashi University of Technology 1-1 Hibarigaoka, Tenpaku, Toyohashi, Aichi 441-8580 Japan;

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原文格式 PDF
正文语种 eng
中图分类自动化技术、计算机技术;
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Stabilizing Image Mosaicing by Model Selection

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