Object tracking under compressed domain

Currently, most approaches for object tracking are under spatial domain using optical flow and depth, or some model-based methods which need to uncompress those video sequences then do further disposal. The computation for uncompressing is expensive and not good for real time control. Although there are also some researchers doing object tracking under compressed domain, they only use part of DCT values of I frames in a video sequence, which doesn't take advantage of the information under compressed domain. In this paper we consider a new method for object tracking which uses the information only supplied in compressed domain through the MPEG encoder. The main scheme we have performed is to get the motion vectors of P and B frames directly from the MPEG video without decompressing it then cluster objects based on the motion vectors. In particular, camera motion is also taken into account since camera's motion can influence the objects' motion and segmentation results dramatically. Experiments based on the method mentioned above have been carried out in several videos. The results obtained indicate that tracking object in compressed domain is very promising.