Adaptive segmentation of moving objects versus background for video coding
Alessandro Neri, Stefania Colonnese, Giuseppe Maria Russo, C. Tabacco · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
In this paper we extend a segmentation method aimed at separating the moving objects from the background in a generic video sequence by means of a higher order statistics (HOS) significance test performed on a group of inter-frame differences. The test is followed by the motion detection phase, producing a preliminary binary segmentation map, that is refined by a final regularization stage. The HOS threshold and the temporal extent of the motion detection phase are adaptively changed on the basis of the estimated background activity and of the detected presence of slowly moving objects. The regularization phase, imposing a local connectivity constraint on the background-foreground map by basic morphological operators, plays an important role in eliminating misclassifications due to motion estimation ambiguities, of the original video sequence. The algorithm performance is illustrated by typical results obtained on MPEG4 sequences.