论文标题
非刚性形状匹配的双重迭代精炼方法
A Dual Iterative Refinement Method for Non-rigid Shape Matching
论文作者
论文摘要
在这项工作中，提出了一种简单有效的双重迭代改进（DIR）方法，用于两个近乎等距形状之间的密集对应关系。关键想法是使用双重信息，例如空间和光谱，或以互补和有效的方式使用局部和全球功能，并从当前迭代中提取更准确的信息以用于下一次迭代。在每个端迭代中，从当前对应开始，每个点的缩放过程都用于通过局部映射失真标准选择匹配良好的锚点。然后使用这些选定的锚定对对齐光谱特征（或其他适当的全局特征），它们的尺寸可适应地匹配所选锚点对的容量。由于以数据自适应方式有效地组合了互补信息，DIR不仅有效，而且在少数迭代中提供了准确的结果。通过选择适当的双重功能，DIR具有处理补丁和部分匹配的灵活性。关于各种数据集的广泛实验表明，就准确性和效率而言，DIR优于其他最先进的方法。
In this work, a simple and efficient dual iterative refinement (DIR) method is proposed for dense correspondence between two nearly isometric shapes. The key idea is to use dual information, such as spatial and spectral, or local and global features, in a complementary and effective way, and extract more accurate information from current iteration to use for the next iteration. In each DIR iteration, starting from current correspondence, a zoom-in process at each point is used to select well matched anchor pairs by a local mapping distortion criterion. These selected anchor pairs are then used to align spectral features (or other appropriate global features) whose dimension adaptively matches the capacity of the selected anchor pairs. Thanks to the effective combination of complementary information in a data-adaptive way, DIR is not only efficient but also robust to render accurate results within a few iterations. By choosing appropriate dual features, DIR has the flexibility to handle patch and partial matching as well. Extensive experiments on various data sets demonstrate the superiority of DIR over other state-of-the-art methods in terms of both accuracy and efficiency.
