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 g
lobal motion components have a fixed relationship from the projection geome
try of camera imaging. Therefore, by examining the measured motion vectors
we are able to group pixels into objects and, at the same time, identify so
me global motion information. In the presence of camera zoom, the object sh
ape is distorted and conventional translational motion estimation may not y
ield accurate motion modeling. A deformable block motion estimation scheme
is thus proposed to estimate the local motion of an object in this situatio
n. Some simulation results are reported. For an artificially generated sequ
ence containing only zoom activity, we find that the maximum estimation err
or in the zoom factor is about 2.8%. Rather good moving object segmentation
results are obtained using the proposed object local motion estimation met
hod after zoom extraction. The deformable block motion compensation is also
Seen to outperform conventional translational block motion compensation fo
r video material containing zoom activity.