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Detection and segmentation of moving objects in complex scenes

Aurélie Bugeau 1 Patrick Pérez 1
1 VISTAS - Spatio-Temporal Vision and Learning
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : In this paper, we address the difficult task of detecting and segmenting foreground moving objects in complex scenes. The sequences we consider exhibit highly dynamic backgrounds, illumination changes and low contrasts, and can have been shot by a moving camera. Three main steps compose the proposed method. First, a set of moving points is selected within a sub-grid of image pixels. A multi-cue descriptor is associated to each of these points. Clusters of points are then formed using a variable bandwidth mean shift technique with automatic bandwidth selection. Finally, segmentation of the object associated to a given cluster is performed using graph cuts. Experiments and comparisons to other motion detection methods on challenging sequences demonstrate the performance of the proposed method for video analysis in complex scenes.
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Submitted on : Friday, October 1, 2010 - 10:59:26 AM
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Aurélie Bugeau, Patrick Pérez. Detection and segmentation of moving objects in complex scenes. Computer Vision and Image Understanding, Elsevier, 2009, pp.ISSN:1077-3142. ⟨10.1016/j.cviu.2008.11.005⟩. ⟨hal-00522620⟩



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