Motion Segment based on Sparse Representation and 3D Features

With the emergence of a large number of 3D human motion capture database, which makes how to efficiently analyze and process the data of human body movement, and make use of the motion capture database become a new challenge. In order to reduce the high dimensional complexity of the data, firstly, a 3D dimensional feature based on 3D spatial and temporal characteristics is extracted from the motion of the human body, then, the motion data is re-expressed by the use of method for sparse representation, and different motion types are separated from long motion sequences, so that a motion database used for subsequent motion recognition and retrieval can be established.