Adapting wavelet compression to human motion capture clips

Motion capture data is an effective way of synthesizing human motion for many interactive applications, including games and simulations. A compact, easy-to-decode representation is needed for the motion data in order to support the real-time motion of a large number of characters with minimal memory and minimal computational overheads. We present a wavelet-based compression technique that is specially adapted to the nature of joint angle data. In particular, we define wavelet coefficient selection as a discrete optimization problem within a tractable search space adapted to the nature of the data. We further extend this technique to take into account visual artifacts such as footskate. The proposed techniques are compared to standard truncated wavelet compression and principal component analysis based compression. The fast decompression times and our focus on short, recomposable animation clips make the proposed techniques a realistic choice for many interactive applications.