Point cloud transport

In this paper we propose a method for temporal interpolation of a point cloud undergoing occlusions and topological changes. The point cloud is first merged into fine clusters, which are then further merged into coarse clusters for each source and target shape. In conjunction with trash box bins to cope with occlusions, a coarse correspondence between a source and a target shape is found that minimizes the transportation cost in the earth mover's distance framework. Subsequently, a fine correspondence is found in a similar way based on the coarse correspondence constraint to suppress locally isolated motion. Finally, the source and target point clouds are transported based on the fine correspondence. Experiments with point cloud sequences captured by a Kinect range finder show promising results.