Generating motion graphs from clusters of individual poses

In this paper, we propose a methodology to generate novel motion clips from existing motion capture data. We present an automated procedure that performs clustering on the data in order to generate a robust and powerful motion graph. We discard the temporal connection between frames during clustering phase, which lets us spot hubs that motions tend to visit more often and use these poses as nodes of our motion graph. This approach greatly reduces computational times and complexity of the final graph structure while maintaining the representational power.