LAUSR

Since existing motion synthesis methods often lack precise controls to the synthesis process, we propose a keyframe-editable motion synthesis framework which allows users to edit the keyframes of an expected motion sequence and use the edited keyframes to control and drive the synthesis process. Specifically, a motion segment can be represented as a start-end frame pair and a group of motion patterns which record the joint angle changing processes between the start and end frames. With the pre-trained paired dictionaries relating the start-end frame space and motion pattern space, we can use the edited keyframe pair to generate its corresponding motion pattern, so the validity of keyframes is very important to the quality of synthesized motions. Thus, we use the probability to measure the motion naturalness and propose a naturalness rectification method to guarantee the validity of the edited keyframes. We also provide a joint-move interface and propose a position refinement method for the detailed adjustment of the joint positions of keyframes. Besides, we add extra naturalness constraint to the motion synthesis process to further improve the naturalness of the generated in- between frames. Extensive rectification experiments in different situations verify the effect of the proposed naturalness rectification model. The comparisons of the synthesis results with other state-of-the-art synthesis methods demonstrate the advantage of our motion synthesis model. The high efficiencies of all the algorithms make the proposed framework competent to the real-time motion synthesis.