Optimization-based key frame extraction for motion capture animation

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• 作者：Xian-mei Liu (1) (2)
  Ai-min Hao (1)
  Dan Zhao (2)
  
• 关键词：Computer animation ; Motion capture ; Key聽frame extraction ; Optimization algorithm
• 刊名：The Visual Computer
• 出版年：2013
• 出版时间：January 2013
• 年：2013
• 卷：29
• 期：1
• 页码：85-95
• 全文大小：997KB
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  15. Lee, J., Chai, J., Reitsma, P.S.A., Hodgins, J.K., Pollard, N.S.: Interactive control of avatars animated with human motion data. ACM Trans. Graph. 21(3), 491鈥?00 (2002)
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• 作者单位：Xian-mei Liu (1) (2)
  Ai-min Hao (1)
  Dan Zhao (2)
  
  1. State Key Laboratory of Virtual Reality Technology and System, Beihang University, Beijing, 100083, China
  2. School of Computer and Information Technology, Northeast Petroleum University, Daqing, 163318, China
  
• ISSN：1432-2315

文摘

In this paper, we present a new solution for extracting key frames from motion capture data using an optimization algorithm to obtain compact and sparse key frame data that can represent the original dense human body motion capture animation. The use of the genetic algorithm helps determine the optimal solution with global exploration capability while the use of a probabilistic simplex method helps expedite the speed of convergence. By finding the chromosome that maximizes the fitness function, the algorithm provides the optimal number of key frames as well as the low reconstruction error with an ordinary interpolation technique. The reconstruction error is computed between the original motion and the reconstruction one by the weighted differences of joint positions and velocities. The resulting set of key frames is obtained by iterative application of the algorithm with initial populations generated randomly and intelligently. We also present experiments which demonstrate that the method can effectively extract key frames with a high compression ratio and reconstruct all other non key frames with high quality.