Key-Postures Based Automated Construction of Motion Graph

STM graph (snap together motion graph), with high degree of polymerization nodes, is a structured graph to describe the relationship of the motion segments in character animation. Nodes in a motion graph serve as postures and edges between these nodes correspond to motion clips. Each node in an STM graph is connected with multiple edges. Many different approaches have been proposed to construct motion graphs from the existing motion capture data, which gives the user a flexible way to synthesize natural looking motion and control the character. So it becomes a hot topic to construct motion graphs automatically. However, the current methods of constructing STM graph depend largely on the experience and manual manipulations. Focusing on the problems mentioned above, a novel method to create motion graph automatically is proposed in this paper. Dimension reduction and nonparametric density estimation analysis are adopted to extract the key postures from motion capture data. The segments are obtained to construct the motion graph with high degree of polymerization nodes. The method not only improves the accuracy of extraction of key postures and reduces the subjective factor, but also improves the flexibility of controlling the virtual characters. Experiments have been done on taekwondo motion clip with 934 frames and badminton motion clip with 1798 frames. The results show the effectiveness of the method.