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中文摘要：
采用线性时不变系统把高维运动数据映射到低维状态空间；在低维状态空间中，定义了姿态之间的相似性度量；并采用误差平方和准则对时序的低维数据点集进行运动分割，分割点上的运动姿态被定义为关键帧．实验结果表明：该算法能够较好地提取出运动序列中的关键帧，并且这些关键帧能够很好地概括原始运动序列的内容．
英文摘要：
Linear time-invariant system is used to derive an explicit mapping between the high- dimensional motion capture data and the low-dimensional state variables. A similarity metric is defined to measure the difference between different poses in the low-dimensional state space, and then the method of mean squared error is employed to divide the motion sequence into a sequence of concatenated segments. The poses at these segmentation points are then defined as keyframes. Experimental results show that the extracted keyframes by our method can give a good visual summarization of the original motion sequence.
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