Source Skeleton: Human
Target Motion Skeleton: Walking Panther
Skeleton correspondence occupies a crucial position in motion retargeting and related animation procedure due to the laborious process of obtaining the appropriate mapping relationship between source and target skeletons. Conventional approaches focused on the objects of similar structure, such as two creatures of same biological species. Hence, we proposed a system to find the correspondence between three-dimensional skeleton structural variations, considered only the structural and topological differences. The proposed system dealt with the strenuous process of mapping skeleton nodes and body-parts in similar and disparate skeleton structural objects by determining the best corresponding skeleton information between two objects with a three-tier mapping algorithm. We evaluated the proposed system through displaying the corresponding node pair of different sets of skeleton structural variations, and performing motion retargeting based on the corresponding result. We also assembled a quantifiable term, Mapped Target Node rate, to describe the mapping result of the node correspondence alongside the animation outcome.
PROJECT MATERIAL: (picture gallery, video, software demo, talk slides, etc.)