Abstract: Motion index tree is constructed based on the hierarchical motion description using dynamic clustering. The example motion is first classified using kNN algorithm according to the motion index tree. Then calculate the similarity between the example and motions in the sub-library through elastic matching. To improve the efficiency, clustering based key frame extraction algorithm is adopted to reduce the feature dimensions. Experiments demonstrate the effectiveness of this algorithm.