Automatic moving object and background separation

Abstract In this paper, we propose a segmentation method of reduced computational complexity aimed at separating the moving objects from the background in a generic video sequence. This task may be accomplished at the coder site to support the functionalities foreseen by new multimedia scenarios, and in particular the content-based functionalities focused by the MPEG-4 activity, allowing the user to access and decode single objects of a video sequence. The proposed algorithm discriminates between background and foreground by means of a higher-order statistics (HOS) significance test performed on a group of inter-frame differences, followed by a motion detection phase, producing a binary segmentation map. The HOS threshold is adaptively changed, based on the estimated background activity and on the potential presence of slowly moving objects. The map is refined by a final regularization stage implemented by means of a cascade of morphological filters. The algorithm performance were tested through the wide experimental activity carried out during the ISO MPEG-4 N2 Core Experiment on Automatic Segmentation Techniques, in which the authors are currently involved. Typical results obtained on MPEG4 sequences are here shown, in order to illustrate the segmentation algorithm performance.

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