Multi-resolution Mean Shift Clustering Algorithm for Shape Interpolation



Hung-Kuo Chu, and Tong-Yee Lee


National Cheng-Kung University, Tainan, Taiwan




In this paper, we solve the problem of 3D shape interpolation with significant pose variation. For an ideal 3D shape interpolation, especially the articulated model, the shape should follow the movement of the underlying articulated structure and be transformed in a way that is as rigid as possible. Given input shapes with compatible connectivity, we propose a novel multiresolution mean shift (MMS) clustering algorithm to automatically extract their near-rigid components. Then, by building the hierarchical relationship among extracted components, we compute a common articulated structure for these input shapes. With the aid of this articulated structure, we solve the shape interpolation by combining 1) a global pose interpolation of near-rigid components from the

source shape to the target shape with 2) a local gradient field interpolation for each pair of components, followed by solving a Poisson equation in order to reconstruct an interpolated shape. As a result, an aesthetically pleasing shape interpolation can be generated, with even the poses of shapes varying significantly. In contrast to a recent state-of-the-art work [19], the proposed approach can achieve comparable or even better results and have better computational efficiency as well.





[Video: Method][Video: Result][Video: Comparison]





IEEE Transactions on Visualization and Computer Graphics, Vol. 15, No. 5, pp. 853-866, 2009


The authors would like to thank anonymous reviewers’ helpful comments to improve this paper. They are also grateful to Niloy J. Mitra and Martin Kilian for their help in performing experimental study with their work [19]. In

addition, they thank AIM@SHAPE Shape Repository and Stanford 3D Scanning Repository for the 3D polyhedral models used in this paper. The eagle and human poses are taken from Poser 7. This work is supported in part by the

Landmark Program of the NCKU Top University Project (Contract B0008), and the National Science Council (Contracts

NSC-97-2628-E-006-125-MY3 and NSC-96-2628-E-006-200-MY3), Taiwan, Republic of China.