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Proceedings Paper

Automatic moving-object and background segmentation by means of higher order statistics
Author(s): Alessandro Neri; Stefania Colonnese; Giuseppe Russo
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Paper Abstract

In this paper we propose a segmentation method aimed at separating the moving objects from the background in a generic video sequence. This task, accomplished at the coder site, is intended to support some new functionalities oriented to access and decode single objects of the coded video sequence, foreseen by innovative multimedia scenarios focused during the MPEG4 work. The proposed segmentation method comprises a motion detection, that produces a preliminary segmentation map, followed by a morphological regularization that plays an important role in eliminating misclassifications due to motion estimation ambiguities, noise, etc., of the original video sequence. The motion detection is essentially based on a higher order statistics (HOS) test that employs a temporally, non-linearly filtered version of the video sequence; this choice is motivated by HOS detection properties. The regularization phase, performed by basic morphological operators, provides a local connectivity constraint on the background-foreground map. The segmentation algorithm performance is illustrated by some experimental results carried out on MPEG4 test sequences.

Paper Details

Date Published: 10 January 1997
PDF: 11 pages
Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); doi: 10.1117/12.263236
Show Author Affiliations
Alessandro Neri, Univ. of Rome III (Italy)
Stefania Colonnese, Fondazione Ugo Bordoni (Italy)
Giuseppe Russo, Fondazione Ugo Bordoni (Italy)

Published in SPIE Proceedings Vol. 3024:
Visual Communications and Image Processing '97
Jan Biemond; Edward J. Delp, Editor(s)

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