SHREC’20: Shape correspondence with non-isometric deformations
Roberto M. Dyke, Yu‐Kun Lai, Paul L. Rosin, Stefano Zappalá, Seana Dykes, Daoliang Guo, Kun Li, Riccardo Marin, Simone Melzi, Jingyu Yang
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.