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首页> 外文会议>International symposium on multispectral image processing and pattern recognition >Geometry and Coherence Based Feature Matching for Structure from Motion
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Geometry and Coherence Based Feature Matching for Structure from Motion

机译：基于几何和相干性的运动结构特征匹配

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摘要

We present a fast feature matching approach based on coherence and geometry constraints. Our method first estimates the epipolar geometry between the images with a small number of feature points, then uses the epipolar geometry constraint and the coherence among the matches to guide the matching of the remaining features. For the rest of the feature points, we firstly reduce the scope of the candidate matching points according to the epipolar geometry constraint. After that, we use the coherence constraint, which requires the matching points of neighboring feature points to be neighbors, to further reduce the number of the candidate matching points. Such a strategy can effectively reduce the matching time and retain more correct matches which are filtered by David Lowe's ratio test. Finally, we remove the mismatches roughly with the coherence among the matches. We validate the effectiveness of our method through matching and SfM results on various of public datasets.
机译：我们提出了一种基于相干性和几何约束的快速特征匹配方法。我们的方法首先估计具有少量特征点的图像之间的对极几何，然后使用对极几何约束和匹配之间的相干性来指导其余特征的匹配。对于其余的特征点，我们首先根据对极几何约束来缩小候选匹配点的范围。此后，我们使用相干约束，该约束要求相邻特征点的匹配点为邻居，以进一步减少候选匹配点的数量。这样的策略可以有效地减少匹配时间，并保留更多正确的匹配，这些匹配由David Lowe的比率测试过滤掉。最后，我们通过匹配之间的一致性大致消除了不匹配。我们通过对各种公共数据集进行匹配和SfM结果来验证我们方法的有效性。

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