Object oriented motion and deformation estimation using composite image segmentation

A novel object oriented motion estimation algorithm is presented. The algorithm provides the means for highly efficient moving image encoding by fully exploiting the temporal redundancy among the objects of successive frames. Two-dimensional segmentation is performed on a composite image synthesised from two consecutive frames. The object correspondence problem is removed implicitly by virtue of the fact that the generated composite segments correspond to successive versions of the same objects. Thus the scheme not only solves the problem of the correspondence between successive versions of the same object, but it also guarantees well matched segments in the presence of noise and varying illumination. Moreover, it preserves motion or deformation information. Progressive motion estimation is achieved within the segmentation process which adapts to the assumed translational or affine model. Motion compensated extrapolation is performed on uncovered background and overlapping regions of the predicted frame. Simulation results prove the efficiency of the predictive scheme even in the case that only motion and deformation parameters need to be transmitted