動作資料(motion capture data)經常被使用在動畫或是遊戲當中，當動作資料增加時，如何讓使用者很快找到想要的資料就成了一個很重要的問題。本篇論文使用了資料探勘(data mining)的技術及分段技術(Segmentation)，將動作資料轉換成視覺化的圖示、圖表，並且為這些資料產生動作摘要，大大的提升了使用者找尋動作資料的方便性。
首先，我們利用了分段演算法，將動作分成兩類：整體運動特徵 (global motion features) 及相對肢體細部特徵 (local motion features)，前者代表身體的旋轉和位移，後者代表四肢的移動。接下來使用了資料探勘中Association Rule的方法，將動作資料分成動作先後發生和動作同時發生兩種，前者表示當某一個動作結束後，發生另一個動作的機率，後者表示當發生某一個動作的同時也發生另一個動作的機率。然後我們將以上兩個的結果整合在一起，產生視覺化的結果：圖示和圖表，以及動作的摘要。最後，我們以數組動作實例展示其方法之可行性及有效性。

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