Vector Space Modeling and Retrieval of Human Motion Capture Data

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.