We propose a method to automatically match two shape collections with a similar shape space structure, e.g. two characters in similar poses, and compute the inter‐maps between the collections. Given the intra‐maps in each collection, we extract the corresponding shape difference operators, and use them to construct an embedding of the shape space of each collection. We then align the two shape spaces, and use the knowledge gained from the alignment to compute the inter‐maps. Unlike existing approaches for collection alignment, our method is applicable to small and large collections alike, and requires no parameter tuning. Furthermore, unlike most approaches for non‐isometric correspondence, our method uses solely the variation within the collection to extract the inter‐maps, and therefore does not require landmarks, descriptors or any additional input. We demonstrate that we achieve high matching accuracy rates, and compute high quality maps on non‐isometric shapes, which compare favorably with automatic state‐of‐the‐art methods for non‐isometric shape correspondence.

中文翻译：

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稳健的形状集合匹配和形状差异的对应

我们提出了一种方法来自动匹配具有相似形状空间结构的两个形状集合，例如两个姿势相似的角色，并计算集合之间的相互映射。给定每个集合中的内部映射，我们提取相应的形状差异算子，并使用它们来构建每个集合的形状空间的嵌入。然后我们对齐两个形状空间，并使用从对齐中获得的知识来计算间映射。与现有的集合对齐方法不同，我们的方法适用于小型和大型集合，并且不需要参数调整。此外，与大多数非等距对应方法不同，我们的方法仅使用集合内的变化来提取内部地图，因此不需要地标，描述符或任何其他输入。我们证明了我们实现了高匹配准确率，并在非等距形状上计算了高质量的地图，这与非等距形状对应的最先进的自动方法相比具有优势。