Symmetry-Aware Mesh Segmentation into Uniform Overlapping Patches

We present intrinsic methods to address the fundamental problem of segmenting a mesh into a specified number of patches with a uniform size and a controllable overlap. Although never addressed in the literature, such a segmentation is useful for a wide range of processing operations where patches represent local regions and overlaps regularize solutions in neighbour patches. Further, we propose a symmetry-aware distance measure and symmetric modification to furthest-point sampling, so that our methods can operate on semantically symmetric meshes. We introduce quantitative measures of patch size uniformity and symmetry, and show that our segmentation outperforms state-of-the-art alternatives in experiments on a well-known dataset. We also use our segmentation in illustrative applications to texture stitching and synthesis where we improve results over state-of-the-art approaches.