Sampling-based Rig Conversion into Non-rigid Helper Bones

Proceedings of the ACM on Computer Graphics and Interactive Techniques, 1(1), Article 13. (ACM SIGGRAPH Symposium on
Interactive 3D Graphics and Games 2018), (to appear).

Authors: Tomohiko Mukai

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Abstract: While 3D animation packages provide a wide variety of animation rigs for creating expressive skin animation, most interactive systems employ linear blend skinning for hard realtime computation. We propose a method for converting an arbitrary skeleton-driven deformer into a linear blend skinning-based helper bone rig. Our system builds the target rig by applying an example-based skinning technique that uses a minimal training dataset obtained from the source model by two-pass sampling of the skin deformation. The first uniform sampling analyzes the relationship between the rotation of each joint and the deformation of skin vertices. The second sampling composes a minimum training dataset by selecting important pose samples using novel geometrical measures. We also propose a skinning decomposition with similarity transformation algorithm for accurately approximating the non-rigid skin deformation behavior by helper bone transformations. Our experimental results demonstrate the proposed automated rig conversion into non-rigid helper bones from several skeleton-driven deformers, including Delta Mush deformers, corrective blendshapes, and virtual-muscle systems.

Acknowledgements: This work was supported by JSPS KAKENHI Grant Number 15K16110, 15H02704. We would like to thank PlatinumGames Inc. for providing useful suggestions and the arm assets.

©ACM 2018. This is the author’s version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the ACM on Computer Graphics and Interactive Techniques, https://doi.org/10.1145/3203190