Volumetric shape contexts for mesh co-segmentation

In the field of mesh segmentation, co-segmentation techniques achieve state-of-the-art performance; however, the segmentation results rely on the shape descriptors used in the segmentation process. In this paper, we propose a novel type of descriptor called the “volumetric shape context” (VSC). For each triangle in the mesh, the VSC describes the distribution of the shape's volume relative to the center of the triangle. This descriptor is descriptive, robust, and invariant under rigid transformations, uniform scaling, mirror imaging and model degeneration. We compare the VSC with state-of-the-art descriptors in a supervised mesh segmentation framework, and the results show that the VSC is most frequently selected as the first descriptor and that combining the VSC with other descriptors improves the segmentation results, thereby demonstrating the descriptiveness of the VSC.