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Robust 2D location of interest points by accumulation

机译:通过累积对兴趣点进行2D定位

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Various interest point and corner definitions were proposed in the past with associated detection algorithms. We propose an intuitive and novel detection algorithm for finding the location of such features in an image. The detection is based on the edges in the original image. Interest points are detected as accumulation points where several edge tangent lines in a neighborhood are crossing. Edge connectivity is not used and thus detected interest points are robust to partial edges, outliers and edge extraction failures at junctions. One advantage of the approach is that detected interest points are not shifted in location when the original image is smoothed compared with other approaches. Experiments performed on Oxford and Cambridge reference databases allow us to show that the proposed detection algorithm performs better than 9 existing interest point detectors in terms of repeatability from multiple camera views.
机译:过去提出了各种兴趣点和角点定义以及相关的检测算法。我们提出了一种直观而新颖的检测算法,用于查找图像中此类特征的位置。该检测基于原始图像中的边缘。将兴趣点检测为附近的几条切线相交的累积点。未使用边缘连通性,因此检测到的兴趣点对结点处的部分边缘,离群值和边缘提取失败具有鲁棒性。该方法的一个优点是,与其他方法相比,当原始图像平滑时,检测到的兴趣点不会在位置上移动。在牛津大学和剑桥大学参考数据库上进行的实验使我们证明,从多个摄像机视角的可重复性来看,所提出的检测算法的性能要优于9个现有的兴趣点检测器。

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