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Finding Corresponding Patches in Texture Images Using Tensor Consistency Check

机译:使用张量一致性检查在纹理图像中找到对应的补丁

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In this paper, we propose a method for finding the corresponding patches across multiple images using tensor consistency check. We assume image correspondences are unknown and the camera sensitivity parameters on intensity are uncalibrated. A patch is defined to be a 2D array/grid of points on a 3D surface. We assume a set of patches are obtained for each view, but the correspondence of individual patches across multiple images is not known. For finding correspondence of these patches, we consider a camera projection model which combines the geometric and photometric information of objects. Furthermore, we consider camera projections in frequency space. By deriving multi view relations in frequency space, we show that we can correctly find the corresponding image patches of 3D surfaces across multiple images. The efficiency of the proposed method is tested using real images.
机译:在本文中,我们提出了一种使用张量一致性检查在多幅图像中查找对应补丁的方法。我们假设图像对应关系未知,并且相机感光度参数在强度上未校准。面片定义为3D曲面上的点的2D阵列/网格。我们假设为每个视图获得一组补丁,但是未知多个图像中各个补丁的对应关系。为了找到这些补丁的对应关系,我们考虑了一个相机投影模型,该模型结合了对象的几何和光度信息。此外,我们考虑了频率空间中的摄像机投影。通过推导频率空间中的多视图关系,我们表明可以正确地找到跨越多个图像的3D表面的相应图像块。使用真实图像测试了所提出方法的效率。

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