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Composition of Complex Motion Models from Elementary Human Motions

机译:由基本人体运动组成的复杂运动模型

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摘要

An appraisal of human motions and particular motion phases is essential for a good interaction between a human and a humanoid robot. We present a new method for the analysis of human motions and the classification of motion phases. The method allows an automatic composition of a motion model for a complex motion from several elementary models. The elementary models can be retrieved from a motion catalogue according to the requirements of a current motion processing task. The method is based on the analysis of the hidden states in a complex HMM and considers the context of all elementary phases in an entire motion sequence. The analysis of motion phases with the new model is computationally more efficient and yields better recognition rates than conventional motion analysis with HMMs and winner-takes-all strategy.
机译:对人类运动和特定运动阶段的评估对于人类与类人机器人之间的良好交互至关重要。我们提出了一种新的方法来分析人体运动和运动阶段的分类。该方法允许从几个基本模型为复杂运动自动合成运动模型。可以根据当前运动处理任务的要求从运动目录中检索基本模型。该方法基于对复杂HMM中隐藏状态的分析,并考虑了整个运动序列中所有基本相位的上下文。与使用HMM和赢家通吃战略的传统运动分析相比,使用新模型进行的运动相位分析在计算上更加高效,并且识别率更高。

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