Real-Time Recognition of Body Motion for Virtual Dance Collaboration System

A method of real-time recognition of body motion for virtual dance collaboration system is described. Fourteen feature values are extracted from motion captured body motion data, and the dimension of data is reduced by using principal component analysis (PCA). In the training phase, templates for motion recognition are constructed from training samples of several types of motion. In the recognition phase, feature values obtained from a real dancer's motion data are projected to the subspace obtained by PCA, and the system recognizes the real dancer's motion by comparing with the motion templates. In this paper, the method and the experiments using seven kinds of basic motions are presented. The recognition experiment proved that the method could be used for motion recognition. A preliminary experiment in which a real dancer and a virtual dancer collaborate with body motion was also carried out.