In this work, a computational method is proposed to automatically investigate the perception of the origin of full-body human movement and its propagation. The method is based on a mathematical game built over a suitably defined graph structure representing the human body. The players of this game are the graph vertices, which form a subset of body joints. Since each vertex contributes to a shared goal (i.e., to the way in which a specific movement-related feature is transferred among the joints), a cooperative game-theoretical model (specifically a transferable-utility game) is adopted, which is able (via the Shapley value) to measure the relevance of the various joints in human movement when performing full-body movement analysis. The method is theoretically investigated and applied to a motion capture dataset obtained from subjects who performed expressive movements. Finally, the method is validated through an online survey, in which several dancers/nondancers participated. The results show the capability of the proposed approach to represent the evolution of the most important joint responsible for originating each dancer's movement.

中文翻译：

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运动起源的自动分析：一种基于图上合作博弈的方法

在这项工作中，提出了一种计算方法来自动研究人体全身运动起源及其传播的感知。该方法基于在代表人体的适当定义的图形结构上构建的数学游戏。这个游戏的参与者是图顶点，它们形成了身体关节的子集。由于每个顶点都有助于共享目标（即特定运动相关特征在关节之间转移的方式），因此采用了合作博弈理论模型（特别是可转移效用博弈），它能够（通过 Shapley 值）来衡量进行全身运动分析时人体运动中各个关节的相关性。该方法在理论上被研究并应用于从执行表现动作的受试者获得的运动捕捉数据集。最后，该方法通过在线调查得到验证，其中有几位舞者/非舞者参与。结果表明，所提出的方法能够代表负责发起每个舞者动作的最重要关节的演变。