Global motion parameter extraction and deformable block motion estimation

Abstract

A global motion parameter estimation method is proposed. The method can be used to segment an image sequence into regions of different moving objects. For any tao pixels belonging to the same moving object, their associated global motion components have a fixed relationship from the projection geometry of camera imaging. Therefore, by examining the measured motion vectors we are able to group pixels into objects and, at the same time, identify some global motion information. In the presence of camera zoom, the object shape is distorted and conventional translational motion estimation may not yield accurate motion modeling. A deformable block motion estimation scheme is thus proposed to estimate the local motion of an object in this situation. Some simulation results are reported. For an artificially generated sequence containing only zoom activity, we find that the maximum estimation error in the zoom factor is about 2.8%. Rather good moving object segmentation results are obtained using the proposed object local motion estimation method after zoom extraction. The deformable block motion compensation is also Seen to outperform conventional translational block motion compensation for video material containing zoom activity.