MDL-based spatiotemporal segmentation from motion in a long image sequence

This paper presents a method for spatiotemporal segmentation of long sequences of images which include multiple independently moving objects, based on the Minimum Description Length (MDL) principle. Spatiotemporal (ST) segments in the image sequence are extracted, each of which consists of edge segments having similar motions. First, we construct a family of motion models, each of which is completely determined by its specified set of equations. Then we formulate the motion description length in a long sequence based on these sets of equations. The motion state of an object at a given moment is determined by finding the model with shortest description length. Temporal segmentation is carried out when the motion state is found to have changed. At the same time, the spatial segmentation is globally optimized in such a way that the motion description of the entire scene reaches a minimum