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首页> 外文期刊>Journal of visual communication & image representation >Bipartite graph-based mismatch removal for wide-baseline image matching
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Bipartite graph-based mismatch removal for wide-baseline image matching

机译：基于二分图的不匹配消除，可实现宽基线图像匹配

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摘要

The conventional wide-baseline image matching aims to establish point-to-point correspondence pairs across the two images under matching. This is normally accomplished by identifying those feature points with most similar local features represented by feature descriptors and measuring the feature-vector distance based on the nearest neighbor matching criterion. However, a large number of mismatches would be incurred especially when the two images under comparison have a large viewpoint variation with respect to each other or involve very different backgrounds. In this paper, a new mismatch removal method is proposed by utilizing the bipartite graph to first establish one-to-one coherent region pairs (CRPs), which are then used to verify whether each point-to-point matching pair is a correct match or not. The generation of CRPs is achieved by applying the Hungarian method to the bipartite graph, together with the use of the proposed region-to-region similarity measurement metric. Extensive experimental results have demonstrated that our proposed mismatch removal method is able to effectively remove a significant number of mismatched point-to-point correspondences.
机译：常规的宽基线图像匹配旨在在匹配下跨两个图像建立点对点对应关系对。通常，这是通过识别那些具有最相似的局部特征（由特征描述符表示）的特征点并基于最近的邻居匹配标准来测量特征向量距离来实现的。然而，特别是当所比较的两个图像相对于彼此具有较大的视点变化或涉及非常不同的背景时，将引起大量的失配。本文提出了一种新的失配消除方法，即利用二部图首先建立一对一的相干区域对（CRP），然后用它们来验证每个点对点匹配对是否正确匹配。或不。通过将匈牙利方法应用于二分图，并使用建议的区域间相似性度量标准，可以实现CRP的生成。大量的实验结果表明，我们提出的失配去除方法能够有效地去除大量不匹配的点对点对应关系。

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