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Image Correspondence from Motion Subspace Constraint and Epipolar Constraint

机译:来自运动子空间约束和eMipolar约束的图像对应

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In this paper, we propose a novel method for inferring image correspondences on the pair of synchronized image sequences. In the proposed method, after tracking the feature points in each image sequence over several frames, we solve the image corresponding problem from two types of geometrical constraints: (1) the motion subspace obtained from the tracked feature points of a target sequence, and (2) the epipolar constraints between the two cameras. Dissimilarly to the conventional correspondence estimation based on image matching using pixel values, the proposed approach enables us to obtain the correspondences even though the feature points, that can be seen from one camera view, but can not be seen (occluded or outside of the view) from the other camera. The validity of our method is demonstrated through the experiments using synthetic and real images.
机译:在本文中,我们提出了一种用于在一对同步图像序列上推断图像对应的新方法。在所提出的方法中,在几个帧上跟踪每个图像序列中的特征点之后,我们从两种类型的几何约束中解决了图像对应的问题:(1)从目标序列的跟踪特征点获得的运动子空间( 2)两个相机之间的末极约束。基于使用像素值的图像匹配的传统对应估计不同,所提出的方法使我们能够从一个摄像机视图中可以看到的特征点,但是不能看到(封闭或在视图之外)获得相应的对应关系)来自其他相机。通过使用合成和真实图像的实验来证明我们的方法的有效性。

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