Search Space Reduction In Motion Matching by Trajectory Clustering

We propose a novel method for the pose selection process in the motion matching technique. This method decreases the amount of calculations of the motion matching system at runtime by limiting the number of poses to be searched, while also reducing the frequency of unwanted pose matches, compared to the preceding methods. We built a table which stores poses classified by their trajectories from the motion data and used it to return a subset of an entire set of poses to be used as a search space in real time.