A 3D Shape Descriptor for Segmentation of Unstructured Meshes into Segment-Wise Coherent Mesh Series

Tomoyuki Mukasa, Shohei Nobuhara, Tony Tung, Takashi Matsuyama

Abstract: This paper presents a novel shape descriptor for topology-based segmentation of 3D video sequence. 3D video is a series of 3D meshes without temporal correspondences which benefit for applications including compression, motion analysis, and kinematic editing. In 3D video, both 3D mesh connectivities and the global surface topology can change frame by frame. This characteristic prevents from making accurate temporal correspondences through the entire 3D mesh series. To overcome this difficulty, we propose a two-step strategy which decomposes the entire sequence into a series of topologically coherent segments using our new shape descriptor, and then estimates temporal correspondences on a per-segment basis. We demonstrate the robustness and accuracy of the shape descriptor on real data which consist of large non-rigid motion and reconstruction errors.