A Descriptor for Voxel Shapes Based on the Skeleton Cut Space

Abstract

Two-dimensional medial axes and three-dimensional curve skeletons have been long used for shape retrieval tasks. In contrast, and despite their ability to fully capture shape geometry and topology, three-dimensional surface skeletons have seen much less usage in this context. We present here a framework for shape matching and retrieval based on such surface skeletons. To this end, we construct a space of cuts generated by the surface skeleton, which has desirable invariance properties with respect to shape size, rotation, translation, pose, and noise. Next, we extract a histogram-based descriptor from this cut space, and discuss three different metrics to compare such histograms for shape retrieval. We illustrate our proposal by showing our descriptor's effectiveness in shape retrieval using a known shape-database benchmark.