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Proceedings Paper

An accurate semi-automatic segmentation scheme based on watershed and change detection mask
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Paper Abstract

This paper presents a region-based segmentation method extracting automatically moving objects from video sequences. Non-moving objects can also be segmented by using a graphical user interface. The segmentation scheme is inspired from existing methods based on the watershed algorithm. The over-segmented regions resulting from the watershed are first organized in a binary partition tree according to a similarity criterion. This tree aims to determine the fusion order. Every region is then fused with the most similar neighbour according to a spatio-temporal criterion regarding the region colors and the temporal colors continuity. The fusion can be stopped either by fixing a priori the final number of regions, or by markers given through the graphical user interface. Markers are also used to assign a class to non-moving objects. Classification of moving objects is automatically obtained by computing the Change Detection Mask. To get a better accuracy on the contours of the segmented objects, we perform a simple post-processing filter to refine the edges between different video object planes.

Paper Details

Date Published: 14 March 2005
PDF: 10 pages
Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005); doi: 10.1117/12.586799
Show Author Affiliations
Cedric De Roover, Univ. Catholique de Louvain (Belgium)
Moncef Gabbouj, Tampere Univ. of Technology (Finland)
Benoit Macq, Univ. Catholique de Louvain (Belgium)

Published in SPIE Proceedings Vol. 5685:
Image and Video Communications and Processing 2005
Amir Said; John G. Apostolopoulos, Editor(s)

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