In this paper, we pose a motion cloning problem of retargeting the motion of a source character to a target character with a different structure. Based on scattered data interpolation, an example-based approach to motion cloning is proposed. Provided with a set of example motions, our method automatically extracts a small number of representative postures called source key-postures. The animator then creates the corresponding keypostures of the target character, breathing his/her imagination and creativity into the output animation. Exploiting this correspondence, each input posture is cloned frame by frame to the target character to produce an initial animation, which is further adjusted in space and time for retargeting and timewarping and then finalized with some interactive fine tuning. With rich animation data available, our motion cloning method aims at rapid prototyping of an animation to verify an animator's concept at an early stage.
Videos taken from a single camera are a most common source of human motions. In this paper, we present a novel method to reconstruct the motion of a human-like figure from inter-frame feature correspondences of a single video stream. We exploit a motion library to resolve the depth ambiguity in recovering the 3D configurations from 2D features. Our reconstruction method takes three major steps: timewarping to align the reference motion with that in the video, reconstructing the joint orientations, and estimating the root trajectory. Experimental results show that our approach can reconstruct highly dynamic motions such as shooting of soccer players, which would be hard to do, otherwise.
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