Isometric Multi-Shape Matching
This work provides a new state-of-the-art method for isometric multi-shape matching, which is relevant for researchers and practitioners in computer vision and graphics working on 3D reconstruction, object tracking, and style transfer.
The paper addresses the problem of finding correspondences between multiple shapes by proposing a novel optimization formulation for isometric multi-shape matching. Their method achieves state-of-the-art performance on various datasets and produces provably cycle-consistent multi-matchings.
Finding correspondences between shapes is a fundamental problem in computer vision and graphics, which is relevant for many applications, including 3D reconstruction, object tracking, and style transfer. The vast majority of correspondence methods aim to find a solution between pairs of shapes, even if multiple instances of the same class are available. While isometries are often studied in shape correspondence problems, they have not been considered explicitly in the multi-matching setting. This paper closes this gap by proposing a novel optimisation formulation for isometric multi-shape matching. We present a suitable optimisation algorithm for solving our formulation and provide a convergence and complexity analysis. Our algorithm obtains multi-matchings that are by construction provably cycle-consistent. We demonstrate the superior performance of our method on various datasets and set the new state-of-the-art in isometric multi-shape matching.