Abstract: For the sake of efficiency and accuracy in retrieving human motions,we model human motion capture data in the form of textual documents and propose a content-based motion retrieval method based on vector space model.In the approach,motion-vocabulary,substantially the most representative human poses,is firstly obtained by applying affinity propagation on the key-pose set which is extracted in advance from database according to upper and lower body respectively.Then motion clips can be represented as motion-documents by replacing each original pose with its closest pose in the motion-vocabulary.Finally we use Bigram vector space model to measure similarities among motions.The approach can automatically index pre-segmented motion clips without human involvement.Experimental results demonstrate the advantages of our approach,both in retrieval accuracy and recall.