ROBUST ESTIMATION OF THE PAN-ZOOM PARAMETERS FROM A BACKGROUND AREA IN CASE OF A CRISS-CROSSING FOREGROUND OBJECT

摘要

In the field of video processing, a model of the background motion has application in deriving depth from motion. The pan-zoom parameters of our background model are estimated from the motion vectors of parts which are a priori likely to belong to the background, such as the top and side borders ("the background area"). This fails when a foreground object obscures the greater part of this background area. We have developed a method to extract a set of pan-zoom parameters for each different part of the background area. Using the pan-zoom parameters of the previous frame, we compute from these sets the pan-zoom parameters most likely to correspond to the proper background parts. This background area partition method gives more accurate pan parameters for shots with the greater part of the background area obscured by one or more foreground objects than application of the entire background area.