论文标题
MAPTREE：在地图空间中恢复多个解决方案
MapTree: Recovering Multiple Solutions in the Space of Maps
论文作者
论文摘要
在本文中，我们提出了一种计算一对3D形状之间多种高质量近乎差异密度对应关系的方法。我们的方法是完全自动的，不依赖用户提供的地标或描述符。这使我们能够分析地图的完整空间并提取多种多样和准确的解决方案，而不是针对大多数先前方法中完成的最佳对应性进行优化。为了实现这一目标，我们根据频谱图表示，提出了一个紧凑的树结构，用于编码和枚举可能的粗糙初始化，并提出一种新颖的有效方法，以精炼它们到密集的点贴图。这导致了一种能够在形状之间产生多个高质量对应关系的新方法，并揭示了没有先验信息的形状的对称结构。此外，我们通过广泛的实验证明我们的方法是鲁棒的，并且比最新的对应关系更准确，以进行形状匹配和对称性检测。
In this paper we propose an approach for computing multiple high-quality near-isometric dense correspondences between a pair of 3D shapes. Our method is fully automatic and does not rely on user-provided landmarks or descriptors. This allows us to analyze the full space of maps and extract multiple diverse and accurate solutions, rather than optimizing for a single optimal correspondence as done in most previous approaches. To achieve this, we propose a compact tree structure based on the spectral map representation for encoding and enumerating possible rough initializations, and a novel efficient approach for refining them to dense pointwise maps. This leads to a new method capable of both producing multiple high-quality correspondences across shapes and revealing the symmetry structure of a shape without a priori information. In addition, we demonstrate through extensive experiments that our method is robust and results in more accurate correspondences than state-of-the-art for shape matching and symmetry detection.
