Finding Kinematic Structure in Time Series Volume Data

This paper presents a new scheme for acquiring 3D kinematic structure and motion from time seriesvolume data. Our basic strategy is to first represent the shape structure of the target in each frame by Reebgraph which we compute by using geodesic distance of target’s surface, and then estimate the kinematicstructure of the target which is consistent with these shape structures. Although the shape structures can bevery different from frame to frame, we propose to derive a unique kinematic structure by way of clusteringsome nodes of graph, based on the fact that they are partly coherent to a certain extent of time series. Oncewe acquire a unique kinematic structure, we fit it to other Reeb graphs in the remaining frames, and describethe motion throughout the entire time series. The only assumption we make is that human body can beapproximated by an articulated body with certain numbers of end-points and branches. We demonstrate theefficacy of the proposed scheme through some experiments.Key Words: Vision-Based Motion Capture, Video and Image Sequence Analysis, Reeb graph, Motion Tracking and Analysis