论文标题
基于简单复合物的点对应关系之间的图像扭曲到歧管上
Simplicial Complex based Point Correspondence between Images warped onto Manifolds
论文作者
论文摘要
最近，投影到多种多样的扭曲图像的可用性（例如，全向球形图像）加上高阶分配方法的成功，引起了人们对搜索改进的高阶匹配算法的兴趣。尽管目前，几种现有的方法“变平”了这样的3D图像使用平面图 /超图匹配方法，但它们仍然患有严重的扭曲和其他不希望的伪影，导致匹配不准确。另外，当前的平面方法不能琐碎地扩展到有效匹配的图像上的点上的点上的点上。因此，在这些扭曲的图像上匹配仍然是一个巨大的挑战。在本文中，我们提出了分配问题，因为在两个图诱导的简单复合物之间找到了徒图，这是图形的高阶类似物。我们提出了一个受约束的二次分配问题（QAP），该问题与简单复合物的每个p骨架匹配，从最高维度到最低维度迭代。我们的方法的准确性和鲁棒性在合成和现实球形 /扭曲（投影）图像上都具有已知地面真相对应关系。在各种数据集上，我们大大优于现有的最新球形匹配方法。
Recent increase in the availability of warped images projected onto a manifold (e.g., omnidirectional spherical images), coupled with the success of higher-order assignment methods, has sparked an interest in the search for improved higher-order matching algorithms on warped images due to projection. Although currently, several existing methods "flatten" such 3D images to use planar graph / hypergraph matching methods, they still suffer from severe distortions and other undesired artifacts, which result in inaccurate matching. Alternatively, current planar methods cannot be trivially extended to effectively match points on images warped onto manifolds. Hence, matching on these warped images persists as a formidable challenge. In this paper, we pose the assignment problem as finding a bijective map between two graph induced simplicial complexes, which are higher-order analogues of graphs. We propose a constrained quadratic assignment problem (QAP) that matches each p-skeleton of the simplicial complexes, iterating from the highest to the lowest dimension. The accuracy and robustness of our approach are illustrated on both synthetic and real-world spherical / warped (projected) images with known ground-truth correspondences. We significantly outperform existing state-of-the-art spherical matching methods on a diverse set of datasets.
