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Robust feature correspondences from a large set of unsorted wide baseline images

机译:来自大量未分类的宽基线图像的鲁棒特征对应

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Given a set of unordered images taken in a wide area, an effective solution is proposed for establishing robust feature correspondences among them. Two major improvements are made in our work as follows: firstly, a robust technique is proposed for the self-organization of a large number of images without spatial orderings; secondly, a novel wide-baseline matching approach is developed to obtain good correspondences over images taken from substantially different viewpoints. The output consists of many sets of reliable pair-wise feature correspondences which are essential in various computer vision applications. Realistic experiments were carried out to evaluate the performances of the proposed method by using a large amount of images captured from our university's campus.
机译:给定一组在广域拍摄的无序图像中,建议在其中建立有效的解决方案。在我们的工作中提出了两项​​重大改进,如下所示:首先,提出了一种稳健的技术,用于在没有空间排序的情况下为大量图像的自组织;其次,开发了一种新的广泛基线匹配方法以获得从基本不同的观点所拍摄的图像的良好对应关系。输出包括许多可靠的配对特征对应关系,这在各种计算机视觉应用中都是必不可少的。进行了现实实验,以评估所提出的方法的性能,使用大学校园捕获的大量图像。

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