Abstract Estimating correspondence between two shapes continues to be a challenging problem in geometry processing. Most current methods assume deformation to be near-isometric, however this is often not the case. For this paper, a collection of shapes of different animals has been curated, where parts of the animals (e.g., mouths, tails & ears) correspond yet are naturally non-isometric. Ground-truth correspondences were established by asking three specialists to independently label corresponding points on each of the models with respect to a previously labelled reference model. We employ an algorithmic strategy to select a single point for each correspondence that is representative of the proposed labels. A novel technique that characterises the sparsity and distribution of correspondences is employed to measure the performance of ten shape correspondence methods.

中文翻译：

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SHREC'20：与非等距变形的形状对应

摘要 估计两个形状之间的对应关系仍然是几何处理中的一个具有挑战性的问题。大多数当前方法假设变形接近等距，但通常情况并非如此。在这篇论文中，收集了不同动物的形状，其中动物的部分（例如嘴、尾巴和耳朵）对应但自然是非等距的。通过要求三位专家相对于先前标记的参考模型独立标记每个模型上的对应点，建立了地面实况对应关系。我们采用算法策略为每个代表建议标签的对应选择一个点。