Optimal and interactive keyframe selection for motion capture

Abstract

Motion capture is increasingly used in games and movies. However, it often requires editing before it can be used. Unfortunately, editing is laborious because of the low-level representation of the data. Existing motion editing methods accomplish modest changes, but larger edits require the artist to "re-animate" the motion by manually selecting a subset of the frames as keyframes. In this paper, we automatically find sets of frames that serve as keyframes for editing the motion. We formulate the problem of selecting an optimal set of keyframes as a type of shortest-path problem, and solve this problem using efficient dynamic programming. Our algorithm can simplify motion capture to around 10% of the original number of frames while retaining most of its detail. By simplifying animation with our algorithm, we realize a new approach to motion editing and stylization founded on the time-tested keyframe interface.