Motion Synthesis Using Style-Editable Inverse Kinematics

摘要

In this paper, a new low-dimensional motion model that can parameterize human motion style is presented. Based on this model, a human motion synthesis approach by using constrainted optimization in a low-dimensional space is proposed. We define a new inverse kinematics solver in this low-dimensional space to generate the required motions meeting user-defined space constraints at key-frames. Our approach can also allow users to edit motion style explicitly by specifying the style parameter. The experimental results demonstrate the effectiveness of this approach which can be used for interactive motion editing.