Robust Global Motion Estimation From Mpeg Streamswith a Gradient Based Refinement

In this paper a new robust algorithm for global motion estimation from an MPEG stream is proposed. The approach is to use a hybrid of two previous global motion estimation algorithms in order to improve the accuracy and robustness of the estimate. The first algorithm is a non-parametric technique which uses the block based motion vectors obtained from an MPEG2 stream and which also generates a coarse background segmentation of the frame. The second algorithm is a gradient based technique which estimates the parameters from the image data directly. In this work, an initial estimate for the global motion is obtained using the non-parametric approach. The parameters are then refined using the gradient based estimation and the segmentation field. This hybrid approach shows significant reduction in mean compensation error over the non-parametric approach. The algorithm is then applied to the problem of mosaicking in sports sequences in which the global motion parameters can be used to make a panorama of an entire shot