基于混合遗传算法的人体运动捕获数据关键帧提取

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Abstract To obtain a compact representation of human motion based on keyframes, a method for keyframes extracting of the captured human motion data by simplex hybrid genetic algorithm is presented, which combines genetic algorithm with a local search technique to converge faster and produce the optimal solution. Firstly, the fitness function is defined to evaluate the availability of keyframe with the goals of minimal reconstruction error and optimal compression rate. Then, the reconstruction error is computed between the original motion and the reconstruction one by the weighted differences of joint positions and velocities. The velocity term helps to preserve the dynamics of motion. Finally, the individuals of initial population are optimized by the knowledge to assure the evolutionary efficiency and the population diversity. Experimental results show that the proposed method can effectively extract keyframes, produce remarkable results in terms of quality and compression ratio, and reconstruct all other non-keyframes of an animation with these keyframes.

Key words： Computer Animation Motion Capture Data Keyframe Extraction Simplex Hybrid Genetic Algorithm

Received: 25 October 2010

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TP391.41

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	Articles by authors
	LIU Xian-Mei
	HAO Ai-Min
	ZHAO Dan

Cite this article:

LIU Xian-Mei,HAO Ai-Min,ZHAO Dan. Keyframe Extraction from Human Motion Capture Databy Simplex Hybrid Genetic Algorithm[J]. , 2011, 24(5): 619-628.

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http://manu46.magtech.com.cn/Jweb_prai/EN/ OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2011/V24/I5/619

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