Adaptive segmentation of moving objects versus background for video coding

Alessandro Neri; Stefania Colonnese; Giuseppe Russo; C. Tabacco

doi:10.1117/12.279565

30 October 1997 Adaptive segmentation of moving objects versus background for video coding

Alessandro Neri, Stefania Colonnese, Giuseppe Russo, C. Tabacco

Proceedings Volume 3164, Applications of Digital Image Processing XX; (1997) https://doi.org/10.1117/12.279565
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

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.

Citation Download Citation

Alessandro Neri, Stefania Colonnese, Giuseppe Russo, and C. Tabacco "Adaptive segmentation of moving objects versus background for video coding", Proc. SPIE 3164, Applications of Digital Image Processing XX, (30 October 1997); https://doi.org/10.1117/12.279565

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