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Performance‐driven motion choreographing with accelerometers

Live performance is an intuitive way to naturally draft the desired motion in the choreographer's mind. In this paper we present a novel approach to choreographing motions by live performance captured with degree of freedom (3‐DOF) accelerometers. The process begins by placing the accelerometers on the user's limbs according to the pre‐specified positions. The computer then recognizes the performed actions using Hidden Markov Model (HMM), which is pre‐trained by the acceleration data samples automatically generated from a pre‐segmented motion capture database. At last, the captured actions are further synthesized with motion retiming and exaggeration based on the acceleration signals from the accelerometers. This method can intuitively rapid‐prototype the choreographed motions for pre‐production of animation, the avatar control in virtual reality and game‐like scenarios, etc. The experimental results show that it can effectively recognize actions with spatial‐time variance, and is easy‐to‐use especially for a novice with little experience. Copyright © 2009 John Wiley & Sons, Ltd.